U.S. patent application number 13/564650 was filed with the patent office on 2013-12-05 for speech recognition adaptation systems based on adaptation data.
This patent application is currently assigned to ELWHA LLC. The applicant listed for this patent is Royce A. Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud. Invention is credited to Royce A. Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud.
Application Number | 20130325449 13/564650 |
Document ID | / |
Family ID | 49671311 |
Filed Date | 2013-12-05 |
United States Patent
Application |
20130325449 |
Kind Code |
A1 |
Levien; Royce A. ; et
al. |
December 5, 2013 |
SPEECH RECOGNITION ADAPTATION SYSTEMS BASED ON ADAPTATION DATA
Abstract
The instant application includes computationally-implemented
systems and methods that include managing adaptation data, wherein
the adaptation data is correlated to at least one aspect of speech
of a particular party, facilitating transmission of the adaptation
data to a target device, wherein the adaptation data is configured
to be applied to the target device to assist in execution of a
speech-facilitated transaction, facilitating reception of
adaptation result data that is based on at least one aspect of the
speech-facilitated transaction between the particular party and the
target device, determining whether to modify the adaptation data at
least partly based on the adaptation result data, and facilitating
transmission of at least a portion of modified adaptation data to a
receiving device. In addition to the foregoing, other aspects are
described in the claims, drawings, and text.
Inventors: |
Levien; Royce A.;
(Lexington, MA) ; Lord; Richard T.; (Tacoma,
WA) ; Lord; Robert W.; (Seattle, WA) ;
Malamud; Mark A.; (Seattle, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Levien; Royce A.
Lord; Richard T.
Lord; Robert W.
Malamud; Mark A. |
Lexington
Tacoma
Seattle
Seattle |
MA
WA
WA
WA |
US
US
US
US |
|
|
Assignee: |
ELWHA LLC
|
Family ID: |
49671311 |
Appl. No.: |
13/564650 |
Filed: |
August 1, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13485733 |
May 31, 2012 |
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13564650 |
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13485738 |
May 31, 2012 |
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13485733 |
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13538855 |
Jun 29, 2012 |
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13485738 |
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13538866 |
Jun 29, 2012 |
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13538855 |
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13564647 |
Aug 1, 2012 |
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13538866 |
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13564649 |
Aug 1, 2012 |
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13564647 |
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Current U.S.
Class: |
704/201 |
Current CPC
Class: |
G10L 15/06 20130101;
G10L 15/30 20130101; G10L 15/063 20130101; G10L 15/065 20130101;
G10L 15/07 20130101 |
Class at
Publication: |
704/201 |
International
Class: |
G10L 19/00 20060101
G10L019/00 |
Claims
1. A computationally-implemented method, comprising: managing
adaptation data, wherein the adaptation data is correlated to at
least one aspect of speech of a particular party; facilitating
transmission of the adaptation data to a target device, wherein the
adaptation data is configured to be applied to the target device to
assist in execution of a speech-facilitated transaction;
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device; determining whether to
modify the adaptation data at least partly based on the adaptation
result data; and facilitating transmission of at least a portion of
modified adaptation data to a receiving device.
2. The computationally-implemented method of claim 1, wherein said
managing adaptation data, wherein the adaptation data is correlated
to at least one aspect of speech of a particular party comprises:
managing data configured to assist in carrying out at least a
portion of a speech transaction conducted by the particular party,
wherein the adaptation data is correlated to at least one aspect of
speech of the particular party.
3-7. (canceled)
8. The computationally-implemented method of claim 1, wherein said
managing adaptation data, wherein the adaptation data is correlated
to at least one aspect of speech of a particular party comprises:
storing adaptation data, wherein the adaptation data is correlated
to at least one aspect of speech of the particular party.
9. The computationally-implemented method of claim 8, wherein said
storing adaptation data, wherein the adaptation data is correlated
to at least one aspect of speech of the particular party comprises:
storing adaptation data at a remote location, wherein the
adaptation data is correlated to at least one aspect of speech of
the particular party.
10. The computationally-implemented method of claim 9, wherein said
storing adaptation data at a remote location, wherein the
adaptation data is correlated to at least one aspect of speech of
the particular party comprises: storing adaptation data at a remote
location at which further adaptation data for at least one further
party is also stored, wherein the adaptation data is correlated to
at least one aspect of speech of the particular party.
11. (canceled)
12. (canceled)
13. The computationally-implemented method of claim 1, wherein said
managing adaptation data, wherein the adaptation data is correlated
to at least one aspect of speech of a particular party comprises:
requesting information regarding a location of the adaptation data
from the particular party.
14. The computationally-implemented method of claim 13, wherein
said requesting information regarding a location of the adaptation
data from the particular party comprises: requesting that the
particular party select a location of the adaptation data from a
list of one or more locations.
15. The computationally-implemented method of claim 14, wherein
said requesting that the particular party select a location of the
adaptation data from a list of one or more locations comprises:
requesting that the particular party select a remote data service
center at which the adaptation data is located from a list of one
or more remote data service centers.
16. (canceled)
17. (canceled)
18. The computationally-implemented method of claim 1, wherein said
facilitating transmission of the adaptation data to a target
device, wherein the adaptation data is configured to be applied to
the target device to assist in execution of a speech-facilitated
transaction comprises: transmitting the adaptation data to the
target device, wherein the adaptation data is configured to be
applied to the target device to assist in execution of the
speech-facilitated transaction.
19-22. (canceled)
23. The computationally-implemented method of claim 1, wherein said
facilitating transmission of the adaptation data to a target
device, wherein the adaptation data is configured to be applied to
the target device to assist in execution of a speech-facilitated
transaction comprises: selecting particular adaptation data from
the adaptation data; and facilitating transmission of the
particular adaptation data to the target device.
24. (canceled)
25. The computationally-implemented method of claim 23, wherein
said selecting particular adaptation data from the adaptation data
comprises: selecting particular adaptation data based on at least
one property of the target device;
26-30. (canceled)
31. The computationally-implemented method of claim 25, wherein
said selecting particular adaptation data based on at least one
property of the target device comprises: receiving information
regarding the property of the target device from the target device;
and selecting the particular adaptation data based on at least the
received property of the target device.
32. The computationally-implemented method of claim 31, wherein
said receiving information regarding the property of the target
device from the target device comprises: receiving a list of at
least one word that the target device commonly receives as a
command, from the target device.
33. The computationally-implemented method of claim 32, wherein
said receiving a list of at least one word that the target device
commonly receives as a command, from the target device comprises:
receiving a list of at least one word that a digital video disc
player commonly receives as a command, from the digital video disc
player.
34. (canceled)
35. The computationally-implemented method of claim 25, wherein
said selecting particular adaptation data based on at least one
property of the target device comprises: selecting a subset of
adaptation data as the particular adaptation data based on a mode
of the target device.
36. The computationally-implemented method of claim 25, wherein
said selecting particular adaptation data based on at least one
property of the target device comprises: selecting a subset of
adaptation data as the particular adaptation data based on a type
of the target device.
37. The computationally-implemented method of claim 36, wherein
said selecting a subset of adaptation data as the particular
adaptation data based on a type of the target device comprises:
selecting a subset of adaptation data that was derived at least in
part from one or more devices of a same type as the target device
as the particular adaptation data, based on a type of the target
device.
38. The computationally-implemented method of claim 37, wherein
said selecting a subset of adaptation data that was derived at
least in part from one or more devices of a same type as the target
device as the particular adaptation data, based on a type of the
target device comprises: selecting a subset of adaptation data that
was derived at least in part from one or more speech interactions
by the particular party with one or more devices of the same type
as the target device as the particular adaptation data, based on a
type of the target device.
39. (canceled)
40. (canceled)
41. The computationally-implemented method of claim 25, wherein
said selecting particular adaptation data based on at least one
property of the target device comprises: selecting a subset of
adaptation data as the particular adaptation data based on a speech
receiving component of the target device.
42. The computationally-implemented method of claim 41, wherein
said selecting a subset of adaptation data as the particular
adaptation data based on a speech receiving component of the target
device comprises: selecting a subset of adaptation data as the
particular adaptation data based on a quality of microphone of the
target device.
43-46. (canceled)
47. The computationally-implemented method of claim 23, wherein
said selecting particular adaptation data from the adaptation data
comprises: selecting particular adaptation data from the adaptation
data based on a condition of an environment in which the
speech-facilitated transaction is configured to be carried out.
48. The computationally-implemented method of claim 47, wherein
said selecting particular adaptation data from the adaptation data
based on a condition of an environment in which the
speech-facilitated transaction is configured to be carried out
comprises: selecting particular adaptation data from the adaptation
data based on an ambient noise level in the environment in which
the speech-facilitated transaction is configured to be carried
out.
49. (canceled)
50. (canceled)
51. The computationally-implemented method of claim 23, wherein
said selecting particular adaptation data from the adaptation data
comprises: receiving a selection of particular adaptation data from
the particular party.
52-56. (canceled)
57. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: receiving
adaptation result data that is based on at least one aspect of the
speech-facilitated transaction between the particular party and the
target device.
58. (canceled)
59. (canceled)
60. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data that is based on a result of
the speech-facilitated transaction between the particular party and
the target device.
61. The computationally-implemented method of claim 60, wherein
said facilitating reception of adaptation result data that is based
on a result of the speech-facilitated transaction between the
particular party and the target device comprises: facilitating
reception of adaptation result data that is based on a measure of
success of at least one portion of the speech-facilitated
transaction between the particular party and the target device.
62. The computationally-implemented method of claim 61, wherein
said facilitating reception of adaptation result data that is based
on a measure of success of at least one portion of the
speech-facilitated transaction between the particular party and the
target device comprises: facilitating reception of adaptation
result data that comprises a representation of success of at least
one portion of the speech-facilitated transaction between the
particular party and the target device.
63-65. (canceled)
66. The computationally-implemented method of claim 62, wherein
said facilitating reception of adaptation result data that
comprises a representation of success of at least one portion of
the speech-facilitated transaction between the particular party and
the target device comprises: facilitating reception of adaptation
result data that comprises a numeric representation of success of
at least one portion of the speech-facilitated transaction between
the particular party and the target device.
67. The computationally-implemented method of claim 66, wherein
said facilitating reception of adaptation result data that
comprises a numeric representation of success of at least one
portion of the speech-facilitated transaction between the
particular party and the target device comprises: facilitating
reception of a confidence rate of correct interpretation of at
least a portion of the speech-facilitated transaction between the
particular party and the target device.
68. The computationally-implemented method of claim 66, wherein
said facilitating reception of adaptation result data that
comprises a numeric representation of success of at least one
portion of the speech-facilitated transaction between the
particular party and the target device comprises: facilitating
reception of an interpretation error rate of at least a portion of
the speech-facilitated transaction between the particular party and
the target device.
69. (canceled)
70. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data comprising a list of at least
one word that was improperly interpreted more than once during the
speech-facilitated transaction.
71. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data comprising a table of at least
one word that was improperly interpreted during the
speech-facilitated transaction, and a number of times that the at
least one word was improperly interpreted during the
speech-facilitated transaction.
72. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data comprising a list of at least
one question that was asked by the target device at least twice
consecutively.
73. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data comprising a table of at least
one question that was asked by the target device at least twice
consecutively, and one or more answers given to the at least one
question by the particular party.
74-77. (canceled)
78. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data upon conclusion of the
speech-facilitated transaction between the particular party and the
target device.
79. (canceled)
80. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data during the speech-facilitated
transaction between the particular party and the target device.
81. The computationally-implemented method of claim 1, wherein said
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device comprises: facilitating
reception of adaptation result data prior to completion of the
speech-facilitated transaction.
82. (canceled)
83. (canceled)
84. The computationally-implemented method of claim 1, wherein said
determining whether to modify the adaptation data at least partly
based on the adaptation result data comprises: determining to
modify the adaptation data when the adaptation result data
indicates that a success of the speech-facilitated transaction is
below a threshold level.
85. The computationally-implemented method of claim 84, wherein
said determining to modify the adaptation data when the adaptation
result data indicates that a success of the speech-facilitated
transaction is below a threshold level comprises: determining to
modify the adaptation data when a success rate of the
speech-facilitated transaction is below a threshold level.
86. The computationally-implemented method of claim 84, wherein
said determining to modify the adaptation data when the adaptation
result data indicates that a success of the speech-facilitated
transaction is below a threshold level comprises: determining to
modify the adaptation data when a number of words that were not
improperly interpreted during the speech-facilitated transaction is
below a threshold level.
87-89. (canceled)
90. The computationally-implemented method of claim 1, wherein said
facilitating transmission of at least a portion of modified
adaptation data to a receiving device comprises: facilitating
transmission of at least a portion of speech of the particular
party that was received as a portion of the adaptation result
data.
91. The computationally-implemented method of claim 1, wherein said
facilitating transmission of at least a portion of modified
adaptation data to a receiving device comprises: facilitating
transmission of at least a portion of modified adaptation data to
the receiving device, wherein the receiving device is the target
device.
92. The computationally-implemented method of claim 91, wherein
said facilitating transmission of at least a portion of modified
adaptation data to the receiving device, wherein the receiving
device is the target device comprises: facilitating transmission of
modified adaptation data to the target device prior to completion
of the speech-facilitated transaction.
93. The computationally-implemented method of claim 91, wherein
said facilitating transmission of at least a portion of modified
adaptation data to the receiving device, wherein the receiving
device is the target device comprises: facilitating transmission of
modified adaptation data to the target device during the
speech-facilitated transaction.
94. (canceled)
95. The computationally-implemented method of claim 91, wherein
said facilitating transmission of at least a portion of modified
adaptation data to the receiving device, wherein the receiving
device is the target device comprises: facilitating transmission of
modified adaptation data to the target device, such that the
modified adaptation data is configured to be applied prior to
completion of the speech-facilitated transaction.
96-99. (canceled)
100. The computationally-implemented method of claim 1, wherein
said facilitating transmission of at least a portion of modified
adaptation data to a receiving device comprises: facilitating
transmission of modified adaptation data to the receiving device,
which is configured to perform a same function as the target
device.
101. The computationally-implemented method of claim 1, wherein
said facilitating transmission of at least a portion of modified
adaptation data to a receiving device comprises: facilitating
transmission of modified adaptation data to the receiving device,
which is a same type as the target device.
102. The computationally-implemented method of claim 1, wherein
said facilitating transmission of at least a portion of modified
adaptation data to a receiving device comprises: transmitting
modified adaptation data from a particular device to the receiving
device.
103. (canceled)
104. The computationally-implemented method of claim 102, wherein
said transmitting modified adaptation data from a particular device
to the receiving device comprises: transmitting modified adaptation
data from a particular device configured to communicate with both
of the target device and the receiving device, to the receiving
device.
105-111. (canceled)
112. A computationally-implemented system, comprising: circuitry
for managing adaptation data, wherein the adaptation data is
correlated to at least one aspect of speech of a particular party;
circuitry for facilitating transmission of the adaptation data to a
target device, wherein the adaptation data is configured to be
applied to the target device to assist in execution of a
speech-facilitated transaction; circuitry for facilitating
reception of adaptation result data that is based on at least one
aspect of the speech-facilitated transaction between the particular
party and the target device; circuitry for determining whether to
modify the adaptation data at least partly based on the adaptation
result data; and circuitry for facilitating transmission of at
least a portion of modified adaptation data to a receiving
device.
113-222. (canceled)
223. A device specified by computational language, comprising: one
or more interchained groups of ordered matter arranged to manage
adaptation data, wherein the adaptation data is correlated to at
least one aspect of speech of a particular party; one or more
interchained groups of ordered matter arranged to facilitate
transmission of the adaptation data to a target device, wherein the
adaptation data is configured to be applied to the target device to
assist in execution of a speech-facilitated transaction; one or
more interchained groups of ordered matter arranged to facilitate
reception of adaptation result data that is based on at least one
aspect of the speech-facilitated transaction between the particular
party and the target device; one or more interchained groups of
ordered matter arranged to determine whether to modify the
adaptation data at least partly based on the adaptation result
data; and one or more interchained groups of ordered matter
arranged to manage transmission of at least a portion of modified
adaptation data to a receiving device.
224. (canceled)
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is related to and claims the benefit
of the earliest available effective filing date(s) from the
following listed application(s) (the "Related Applications") (e.g.,
claims earliest available priority dates for other than provisional
patent applications or claims benefits under 35 USC .sctn.119(e)
for provisional patent applications, for any and all parent,
grandparent, great-grandparent, etc. applications of the Related
Application(s)). All subject matter of the Related Applications and
of any and all parent, grandparent, great-grandparent, etc.
applications of the Related Applications, including any priority
claims, is incorporated herein by reference to the extent such
subject matter is not inconsistent herewith.
RELATED APPLICATIONS
[0002] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application Ser. No. 13/485,733, entitled SPEECH RECOGNITION
ADAPTATION SYSTEMS BASED ON ADAPTATION DATA, naming Royce A.
Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud, and John
D. Rinaldo, Jr. as inventors, filed 31 May 2012, which is currently
co-pending or is an application of which a currently co-pending
application is entitled to the benefit of the filing date.
[0003] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application Ser. No. 13/485,738, entitled SPEECH RECOGNITION
ADAPTATION SYSTEMS BASED ON ADAPTATION DATA, naming Royce A.
Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud, and John
D. Rinaldo, Jr. as inventors, filed 31 May 2012, which is currently
co-pending or is an application of which a currently co-pending
application is entitled to the benefit of the filing date.
[0004] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application Ser. No. 13/538,855, entitled SPEECH RECOGNITION
ADAPTATION SYSTEMS BASED ON ADAPTATION DATA, naming Royce A.
Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud, and John
D. Rinaldo, Jr. as inventors, filed 29 Jun. 2012, which is
currently co-pending or is an application of which a currently
co-pending application is entitled to the benefit of the filing
date.
[0005] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application Ser. No. 13/538,866, entitled SPEECH RECOGNITION
ADAPTATION SYSTEMS BASED ON ADAPTATION DATA, naming Royce A.
Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud, and John
D. Rinaldo, Jr. as inventors, filed 29 Jun. 2012, which is
currently co-pending or is an application of which a currently
co-pending application is entitled to the benefit of the filing
date.
[0006] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application Ser. No. To Be Assigned, entitled SPEECH
RECOGNITION ADAPTATION SYSTEMS BASED ON ADAPTATION DATA, naming
Royce A. Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud,
and John D. Rinaldo, Jr. as inventors, filed 1 Aug. 2012, which is
currently co-pending or is an application of which a currently
co-pending application is entitled to the benefit of the filing
date.
[0007] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application Ser. No. To Be Assigned, entitled SPEECH
RECOGNITION ADAPTATION SYSTEMS BASED ON ADAPTATION DATA, naming
Royce A. Levien, Richard T. Lord, Robert W. Lord, Mark A. Malamud,
and John D. Rinaldo, Jr. as inventors, filed 1 Aug. 2012, which is
currently co-pending or is an application of which a currently
co-pending application is entitled to the benefit of the filing
date.
[0008] The United States Patent Office (USPTO) has published a
notice to the effect that the USPTO's computer programs require
that patent applicants reference both a serial number and indicate
whether an application is a continuation, continuation-in-part, or
divisional of a parent application. Stephen G. Kunin, Benefit of
Prior-Filed Application, USPTO Official Gazette Mar. 18, 2003. The
present Applicant Entity (hereinafter "Applicant") has provided
above a specific reference to the application(s) from which
priority is being claimed as recited by statute. Applicant
understands that the statute is unambiguous in its specific
reference language and does not require either a serial number or
any characterization, such as "continuation" or
"continuation-in-part," for claiming priority to U.S. patent
applications. Notwithstanding the foregoing, Applicant understands
that the USPTO's computer programs have certain data entry
requirements, and hence Applicant has provided designation(s) of a
relationship between the present application and its parent
application(s) as set forth above, but expressly points out that
such designation(s) are not to be construed in any way as any type
of commentary and/or admission as to whether or not the present
application contains any new matter in addition to the matter of
its parent application(s).
BACKGROUND
[0009] This application is related to portable speech adaptation
data.
SUMMARY
[0010] A computationally implemented method includes, but is not
limited to, managing adaptation data, wherein the adaptation data
is correlated to at least one aspect of speech of a particular
party, facilitating transmission of the adaptation data to a target
device, wherein the adaptation data is configured to be applied to
the target device to assist in execution of a speech-facilitated
transaction, facilitating reception of adaptation result data that
is based on at least one aspect of the speech-facilitated
transaction between the particular party and the target device,
determining whether to modify the adaptation data at least partly
based on the adaptation result data, and facilitating transmission
of at least a portion of modified adaptation data to a receiving
device. In addition to the foregoing, other method aspects are
described in the claims, drawings, and text forming a part of the
present disclosure.
[0011] In one or more various aspects, related systems include but
are not limited to circuitry and/or programming for effecting the
herein referenced method aspects; the circuitry and/or programming
can be virtually any combination of hardware, software, and/or
firmware in one or more machines or article of manufacture
configured to effect the herein-referenced method aspects depending
upon the design choices of the system designer.
[0012] A computationally-implemented system includes, but is not
limited to, means for managing adaptation data, wherein the
adaptation data is correlated to at least one aspect of speech of a
particular party, means for facilitating transmission of the
adaptation data to a target device, wherein the adaptation data is
configured to be applied to the target device to assist in
execution of a speech-facilitated transaction, one or more
instructions for facilitating reception of adaptation result data
that is based on at least one aspect of the speech-facilitated
transaction between the particular party and the target device,
means for determining whether to modify the adaptation data at
least partly based on the adaptation result data, and means for
facilitating transmission of at least a portion of modified
adaptation data to a receiving device. In addition to the
foregoing, other system aspects are described in the claims,
drawings, and text forming a part of the present disclosure.
[0013] A computationally-implemented system includes, but is not
limited to circuitry for managing adaptation data, wherein the
adaptation data is correlated to at least one aspect of speech of a
particular party, circuitry for facilitating transmission of the
adaptation data to a target device, wherein the adaptation data is
configured to be applied to the target device to assist in
execution of a speech-facilitated transaction, circuitry for
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device, circuitry for
determining whether to modify the adaptation data at least partly
based on the adaptation result data, and circuitry for facilitating
transmission of at least a portion of modified adaptation data to a
receiving device. In addition to the foregoing, other system
aspects are described in the claims, drawings, and text forming a
part of the present disclosure.
[0014] A computer program product comprising an article of
manufacture bears instructions including, but not limited to, one
or more instructions for managing adaptation data, wherein the
adaptation data is correlated to at least one aspect of speech of a
particular party, one or more instructions for facilitating
transmission of the adaptation data to a target device, wherein the
adaptation data is configured to be applied to the target device to
assist in execution of a speech-facilitated transaction, one or
more instructions for facilitating reception of adaptation result
data that is based on at least one aspect of the speech-facilitated
transaction between the particular party and the target device, one
or more instructions for determining whether to modify the
adaptation data at least partly based on the adaptation result
data, and one or more instructions for facilitating transmission of
at least a portion of modified adaptation data to a receiving
device. In addition to the foregoing, other computer program
product aspects are described in the claims, drawings, and text
forming a part of the present disclosure.
[0015] A device specified by computational language includes, but
is not limited to, one or more interchained groups of ordered
matter arranged to manage adaptation data, wherein the adaptation
data is correlated to at least one aspect of speech of a particular
party, one or more interchained groups of ordered matter arranged
to facilitate transmission of the adaptation data to a target
device, wherein the adaptation data is configured to be applied to
the target device to assist in execution of a speech-facilitated
transaction, one or more interchained groups of ordered matter
arranged to facilitate reception of adaptation result data that is
based on at least one aspect of the speech-facilitated transaction
between the particular party and the target device, one or more
interchained groups of ordered matter arranged to determine whether
to modify the adaptation data at least partly based on the
adaptation result data, and one or more interchained groups of
ordered matter arranged to manage transmission of at least a
portion of modified adaptation data to a receiving device. In
addition to the foregoing, other hardware aspects are described in
the claims, drawings, and text forming a part of the present
disclosure.
[0016] A computer architecture comprising at least one level,
includes, but is not limited to, architecture configured to be
managing adaptation data, wherein the adaptation data is correlated
to at least one aspect of speech of a particular party,
architecture configured to be facilitating transmission of the
adaptation data to a target device, wherein the adaptation data is
configured to be applied to the target device to assist in
execution of a speech-facilitated transaction, architecture
configured to be facilitating reception of adaptation result data
that is based on at least one aspect of the speech-facilitated
transaction between the particular party and the target device,
architecture configured to be determining whether to modify the
adaptation data at least partly based on the adaptation result
data, and architecture configured to be facilitating transmission
of at least a portion of modified adaptation data to a receiving
device. In addition to the foregoing, other architecture aspects
are described in the claims, drawings, and text forming a part of
the present disclosure.
[0017] The foregoing summary is illustrative only and is not
intended to be in any way limiting. In addition to the illustrative
aspects, embodiments, and features described above, further
aspects, embodiments, and features will become apparent by
reference to the drawings and the following detailed
description.
BRIEF DESCRIPTION OF THE FIGURES
[0018] FIG. 1, including FIGS. 1A and 1B, shows a high-level block
diagram of a personal device 120 operating in an exemplary
environment 100, according to an embodiment.
[0019] FIG. 2, including FIGS. 2A-2C, shows a particular
perspective of the adaptation data correlated to at least one
particular party speech aspect managing module 152 of the personal
device 120 of environment 100 of FIG. 1.
[0020] FIG. 3, including FIGS. 3A-3G, shows a particular
perspective of the adaptation data transmission to target device
facilitating module 154 of the personal device 120 of environment
100 of FIG. 1.
[0021] FIG. 4, including FIGS. 4A-4E, shows a particular
perspective of the adaptation result data based on a result of at
least one aspect of a speech-facilitated transaction reception
facilitating module 156 of the personal device 120 of environment
100 of FIG. 1.
[0022] FIG. 5, including FIGS. 5A-5B, shows a particular
perspective of the adaptation data modification determining at
least partly based on adaptation result data module 158 of the
personal device 120 of environment 100 of FIG. 1.
[0023] FIG. 6, including FIGS. 6A-6D, shows a particular
perspective of the at least a portion of modified adaptation data
transmission to receiving device facilitating module 160 of the
personal device 120 of environment 100 of FIG. 1.
[0024] FIG. 7 is a high-level logic flowchart of a process, e.g.,
operational flow 700, according to an embodiment.
[0025] FIG. 8A is a high-level logic flowchart of a process
depicting alternate implementations of a managing adaptation data
operation 702 of FIG. 7.
[0026] FIG. 8B is a high-level logic flowchart of a process
depicting alternate implementations of a managing adaptation data
operation 702 of FIG. 7.
[0027] FIG. 8C is a high-level logic flowchart of a process
depicting alternate implementations of a managing adaptation data
operation 702 of FIG. 7.
[0028] FIG. 8D is a high-level logic flowchart of a process
depicting alternate implementations of a managing adaptation data
operation 702 of FIG. 7.
[0029] FIG. 9A is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0030] FIG. 9B is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0031] FIG. 9C is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0032] FIG. 9D is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0033] FIG. 9E is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0034] FIG. 9F is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0035] FIG. 9G is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data
transmission facilitating operation 704 of FIG. 7.
[0036] FIG. 10A is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation result data
reception facilitating operation 706 of FIG. 7.
[0037] FIG. 10B is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation result data
reception facilitating operation 706 of FIG. 7.
[0038] FIG. 10C is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation result data
reception facilitating operation 706 of FIG. 7.
[0039] FIG. 10D is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation result data
reception facilitating operation 706 of FIG. 7.
[0040] FIG. 10E is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation result data
reception facilitating operation 706 of FIG. 7.
[0041] FIG. 11A is a high-level logic flowchart of an adaptation
data modification determining operation 708 of FIG. 7.
[0042] FIG. 11B is a high-level logic flowchart of an adaptation
data modification determining operation 708 of FIG. 7.
[0043] FIG. 12A is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data portion
transmission facilitating operation 710 of FIG. 7.
[0044] FIG. 12B is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data portion
transmission facilitating operation 710 of FIG. 7.
[0045] FIG. 12C is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data portion
transmission facilitating operation 710 of FIG. 7.
[0046] FIG. 12D is a high-level logic flowchart of a process
depicting alternate implementations of an adaptation data portion
transmission facilitating operation 710 of FIG. 7.
DETAILED DESCRIPTION
[0047] In the following detailed description, reference is made to
the accompanying drawings, which form a part hereof. In the
drawings, similar symbols typically identify similar or identical
components or items, unless context dictates otherwise. The
illustrative embodiments described in the detailed description,
drawings, and claims are not meant to be limiting. Other
embodiments may be utilized, and other changes may be made, without
departing from the spirit or scope of the subject matter presented
here.
[0048] The proliferation of automation in many transactions is
apparent. For example, Automated Teller Machines ("ATMs") dispense
money and receive deposits. Airline ticket counter machines check
passengers in, dispense tickets, and allow passengers to change or
upgrade flights. Train and subway ticket counter machines allow
passengers to purchase a ticket to a particular destination without
invoking a human interaction at all. Many groceries and pharmacies
have self-service checkout machines which allow a consumer to pay
for goods purchased by interacting only with a machine. Large
companies now staff telephone answering systems with machines that
interact with customers, and invoke a human in the transaction only
if there is a problem with the machine-facilitated transaction.
[0049] Nevertheless, as such automation increases, convenience and
accessibility may decrease. Self-checkout machines at grocery
stores may be difficult to operate. ATMs and ticket counter
machines may be mostly inaccessible to disabled persons or persons
requiring special access. Where before, the interaction with a
human would allow disabled persons to complete transactions with
relative ease, if a disabled person is unable to push the buttons
on an ATM, there is little the machine can do to facilitate the
transaction to completion. While some of these public terminals
allow speech operations, they are configured to the most generic
forms of speech, which may be less useful in recognizing particular
speakers, thereby leading to frustration for users attempting to
speak to the machine. This problem may be especially challenging
for the disabled, who already may face significant challenges in
completing transactions with automated machines.
[0050] In addition, smartphones and tablet devices also now are
configured to receive speech commands. Speech and voice controlled
automobile systems now appear regularly in motor vehicles, even in
economical, mass-produced vehicles. Home entertainment devices,
e.g., disc players, televisions, radios, stereos, and the like, may
respond to speech commands. Additionally, home security systems may
respond to speech commands. In an office setting, a worker's
computer may respond to speech from that worker, allowing faster,
more efficient work flows. Such systems and machines may be trained
to operate with particular users, either through explicit training
or through repeated interactions. Nevertheless, when that system is
upgraded or replaced, e.g., a new TV is bought, that training may
be lost with the device.
[0051] Thus, adaptation data for speech recognition systems may be
separated from the device which recognizes the speech, and may be
more closely associated with a user, e.g., through a device carried
by the user, or through a network location associated with the
user. In accordance with various embodiments, computationally
implemented methods, systems, circuitry, articles of manufacture,
and computer program products are designed to, among other things,
provide an interface for managing adaptation data, wherein the
adaptation data is correlated to at least one aspect of speech of a
particular party, an interface for facilitating transmission of the
adaptation data to a target device, wherein the adaptation data is
configured to be applied to the target device to assist in
execution of a speech-facilitated transaction, an interface for
facilitating reception of adaptation result data that is based on
at least one aspect of the speech-facilitated transaction between
the particular party and the target device, an interface for
determining whether to modify the adaptation data at least partly
based on the adaptation result data, and an interface for
facilitating transmission of at least a portion of modified
adaptation data to a receiving device.
[0052] The foregoing summary is illustrative only and is not
intended to be in any way limiting. In addition to the illustrative
aspects, embodiments, and features described above, further
aspects, embodiments, and features will become apparent by
reference to the drawings and the following detailed
description.
[0053] The claims, description, and drawings of this application
may describe one or more of the instant technologies in
operational/functional language, for example as a set of operations
to be performed by a computer. Such operational/functional
description in most instances would be understood by one skilled
the art as specifically-configured hardware (e.g., because a
general purpose computer in effect becomes a special purpose
computer once it is programmed to perform particular functions
pursuant to instructions from program software).
[0054] Importantly, although the operational/functional
descriptions described herein are understandable by the human mind,
they are not abstract ideas of the operations/functions divorced
from computational implementation of those operations/functions.
Rather, the operations/functions represent a specification for the
massively complex computational machines or other means. As
discussed in detail below, the operational/functional language must
be read in its proper technological context, i.e., as concrete
specifications for physical implementations.
[0055] The logical operations/functions described herein are a
distillation of machine specifications or other physical mechanisms
specified by the operations/functions such that the otherwise
inscrutable machine specifications may be comprehensible to the
human mind. The distillation also allows one of skill in the art to
adapt the operational/functional description of the technology
across many different specific vendors' hardware configurations or
platforms, without being limited to specific vendors' hardware
configurations or platforms.
[0056] Some of the present technical description (e.g., detailed
description, drawings, claims, etc.) may be set forth in terms of
logical operations/functions. As described in more detail in the
following paragraphs, these logical operations/functions are not
representations of abstract ideas, but rather representative of
static or sequenced specifications of various hardware elements.
Differently stated, unless context dictates otherwise, the logical
operations/functions will be understood by those of skill in the
art to be representative of static or sequenced specifications of
various hardware elements. This is true because tools available to
one of skill in the art to implement technical disclosures set
forth in operational/functional formats--tools in the form of a
high-level programming language (e.g., C, java, visual basic),
etc.), or tools in the form of Very high speed Hardware Description
Language ("VHDL," which is a language that uses text to describe
logic circuits)--are generators of static or sequenced
specifications of various hardware configurations. This fact is
sometimes obscured by the broad term "software," but, as shown by
the following explanation, those skilled in the art understand that
what is termed "software" is a shorthand for a massively complex
interchaining/specification of ordered-matter elements. The term
"ordered-matter elements" may refer to physical components of
computation, such as assemblies of electronic logic gates,
molecular computing logic constituents, quantum computing
mechanisms, etc.
[0057] For example, a high-level programming language is a
programming language with strong abstraction, e.g., multiple levels
of abstraction, from the details of the sequential organizations,
states, inputs, outputs, etc., of the machines that a high-level
programming language actually specifies. See, e.g., Wikipedia,
High-level programming language,
http://en.wikipedia.org/wiki/High-levelprogramming_language (as of
Jun. 5, 2012, 21:00 GMT). In order to facilitate human
comprehension, in many instances, high-level programming languages
resemble or even share symbols with natural languages. See, e.g.,
Wikipedia, Natural language,
http://en.wikipedia.org/wiki/Natural_language (as of Jun. 5, 2012,
21:00 GMT).
[0058] It has been argued that because high-level programming
languages use strong abstraction (e.g., that they may resemble or
share symbols with natural languages), they are therefore a "purely
mental construct." (e.g., that "software"--a computer program or
computer programming--is somehow an ineffable mental construct,
because at a high level of abstraction, it can be conceived and
understood in the human mind). This argument has been used to
characterize technical description in the form of
functions/operations as somehow "abstract ideas." In fact, in
technological arts (e.g., the information and communication
technologies) this is not true.
[0059] The fact that high-level programming languages use strong
abstraction to facilitate human understanding should not be taken
as an indication that what is expressed is an abstract idea. In
fact, those skilled in the art understand that just the opposite is
true. If a high-level programming language is the tool used to
implement a technical disclosure in the form of
functions/operations, those skilled in the art will recognize that,
far from being abstract, imprecise, "fuzzy," or "mental" in any
significant semantic sense, such a tool is instead a near
incomprehensibly precise sequential specification of specific
computational machines--the parts of which are built up by
activating/selecting such parts from typically more general
computational machines over time (e.g., clocked time). This fact is
sometimes obscured by the superficial similarities between
high-level programming languages and natural languages. These
superficial similarities also may cause a glossing over of the fact
that high-level programming language implementations ultimately
perform valuable work by creating/controlling many different
computational machines.
[0060] The many different computational machines that a high-level
programming language specifies are almost unimaginably complex. At
base, the hardware used in the computational machines typically
consists of some type of ordered matter (e.g., traditional
electronic devices (e.g., transistors), deoxyribonucleic acid
(DNA), quantum devices, mechanical switches, optics, fluidics,
pneumatics, optical devices (e.g., optical interference devices),
molecules, etc.) that are arranged to form logic gates. Logic gates
are typically physical devices that may be electrically,
mechanically, chemically, or otherwise driven to change physical
state in order to create a physical reality of Boolean logic
[0061] Logic gates may be arranged to form logic circuits, which
are typically physical devices that may be electrically,
mechanically, chemically, or otherwise driven to create a physical
reality of certain logical functions. Types of logic circuits
include such devices as multiplexers, registers, arithmetic logic
units (ALUs), computer memory, etc., each type of which may be
combined to form yet other types of physical devices, such as a
central processing unit (CPU)--the best known of which is the
microprocessor. A modern microprocessor will often contain more
than one hundred million logic gates in its many logic circuits
(and often more than a billion transistors). See, e.g., Wikipedia,
Logic gates, http://en.wikipedia.org/wiki/Logic_gates (as of Jun.
5, 2012, 21:03 GMT).
[0062] The logic circuits forming the microprocessor are arranged
to provide a microarchitecture that will carry out the instructions
defined by that microprocessor's defined Instruction Set
Architecture. The Instruction Set Architecture is the part of the
microprocessor architecture related to programming, including the
native data types, instructions, registers, addressing modes,
memory architecture, interrupt and exception handling, and external
Input/Output. See, e.g., Wikipedia, Computer architecture,
http://en.wikipedia.org/wiki/Computer_architecture (as of Jun. 5,
2012, 21:03 GMT).
[0063] The Instruction Set Architecture includes a specification of
the machine language that can be used by programmers to use/control
the microprocessor. Since the machine language instructions are
such that they may be executed directly by the microprocessor,
typically they consist of strings of binary digits, or bits. For
example, a typical machine language instruction might be many bits
long (e.g., 32, 64, or 128 bit strings are currently common). A
typical machine language instruction might take the form
"11110000101011110000111100111111" (a 32 bit instruction).
[0064] It is significant here that, although the machine language
instructions are written as sequences of binary digits, in
actuality those binary digits specify physical reality. For
example, if certain semiconductors are used to make the operations
of Boolean logic a physical reality, the apparently mathematical
bits "1" and "0" in a machine language instruction actually
constitute a shorthand that specifies the application of specific
voltages to specific wires. For example, in some semiconductor
technologies, the binary number "1" (e.g., logical "1") in a
machine language instruction specifies around +5 volts applied to a
specific "wire" (e.g., metallic traces on a printed circuit board)
and the binary number "0" (e.g., logical "0") in a machine language
instruction specifies around -5 volts applied to a specific "wire."
In addition to specifying voltages of the machines' configuration,
such machine language instructions also select out and activate
specific groupings of logic gates from the millions of logic gates
of the more general machine. Thus, far from abstract mathematical
expressions, machine language instruction programs, even though
written as a string of zeros and ones, specify many, many
constructed physical machines or physical machine states.
[0065] Machine language is typically incomprehensible by most
humans (e.g., the above example was just ONE instruction, and some
personal computers execute more than two billion instructions every
second). See, e.g., Wikipedia, Instructions per second,
http://en.wikipedia.org/wiki/Instructions_per_second (as of Jun. 5,
2012, 21:04 GMT).
[0066] Thus, programs written in machine language--which may be
tens of millions of machine language instructions long--are
incomprehensible. In view of this, early assembly languages were
developed that used mnemonic codes to refer to machine language
instructions, rather than using the machine language instructions'
numeric values directly (e.g., for performing a multiplication
operation, programmers coded the abbreviation "mult," which
represents the binary number "011000" in MIPS machine code). While
assembly languages were initially a great aid to humans controlling
the microprocessors to perform work, in time the complexity of the
work that needed to be done by the humans outstripped the ability
of humans to control the microprocessors using merely assembly
languages.
[0067] At this point, it was noted that the same tasks needed to be
done over and over, and the machine language necessary to do those
repetitive tasks was the same. In view of this, compilers were
created. A compiler is a device that takes a statement that is more
comprehensible to a human than either machine or assembly language,
such as "add 2+2 and output the result," and translates that human
understandable statement into a complicated, tedious, and immense
machine language code (e.g., millions of 32, 64, or 128 bit length
strings). Compilers thus translate high-level programming language
into machine language.
[0068] This compiled machine language, as described above, is then
used as the technical specification which sequentially constructs
and causes the interoperation of many different computational
machines such that humanly useful, tangible, and concrete work is
done. For example, as indicated above, such machine language--the
compiled version of the higher-level language--functions as a
technical specification which selects out hardware logic gates,
specifies voltage levels, voltage transition timings, etc., such
that the humanly useful work is accomplished by the hardware.
[0069] Thus, a functional/operational technical description, when
viewed by one of skill in the art, is far from an abstract idea.
Rather, such a functional/operational technical description, when
understood through the tools available in the art such as those
just described, is instead understood to be a humanly
understandable representation of a hardware specification, the
complexity and specificity of which far exceeds the comprehension
of most any one human. With this in mind, those skilled in the art
will understand that any such operational/functional technical
descriptions--in view of the disclosures herein and the knowledge
of those skilled in the art--may be understood as operations made
into physical reality by (a) one or more interchained physical
machines, (b) interchained logic gates configured to create one or
more physical machine(s) representative of sequential/combinatorial
logic(s), (c) interchained ordered matter making up logic gates
(e.g., interchained electronic devices (e.g., transistors), DNA,
quantum devices, mechanical switches, optics, fluidics, pneumatics,
molecules, etc.) that create physical reality representative of
logic(s), or (d) virtually any combination of the foregoing.
Indeed, any physical object which has a stable, measurable, and
changeable state may be used to construct a machine based on the
above technical description. Charles Babbage, for example,
constructed the first computer out of wood and powered by cranking
a handle.
[0070] Thus, far from being understood as an abstract idea, those
skilled in the art will recognize a functional/operational
technical description as a humanly-understandable representation of
one or more almost unimaginably complex and time sequenced hardware
instantiations. The fact that functional/operational technical
descriptions might lend themselves readily to high-level computing
languages (or high-level block diagrams for that matter) that share
some words, structures, phrases, etc. with natural language simply
cannot be taken as an indication that such functional/operational
technical descriptions are abstract ideas, or mere expressions of
abstract ideas. In fact, as outlined herein, in the technological
arts this is simply not true. When viewed through the tools
available to those of skill in the art, such functional/operational
technical descriptions are seen as specifying hardware
configurations of almost unimaginable complexity.
[0071] As outlined above, the reason for the use of
functional/operational technical descriptions is at least twofold.
First, the use of functional/operational technical descriptions
allows near-infinitely complex machines and machine operations
arising from interchained hardware elements to be described in a
manner that the human mind can process (e.g., by mimicking natural
language and logical narrative flow). Second, the use of
functional/operational technical descriptions assists the person of
skill in the art in understanding the described subject matter by
providing a description that is more or less independent of any
specific vendor's piece(s) of hardware.
[0072] The use of functional/operational technical descriptions
assists the person of skill in the art in understanding the
described subject matter since, as is evident from the above
discussion, one could easily, although not quickly, transcribe the
technical descriptions set forth in this document as trillions of
ones and zeroes, billions of single lines of assembly-level machine
code, millions of logic gates, thousands of gate arrays, or any
number of intermediate levels of abstractions. However, if any such
low-level technical descriptions were to replace the present
technical description, a person of skill in the art could encounter
undue difficulty in implementing the disclosure, because such a
low-level technical description would likely add complexity without
a corresponding benefit (e.g., by describing the subject matter
utilizing the conventions of one or more vendor-specific pieces of
hardware). Thus, the use of functional/operational technical
descriptions assists those of skill in the art by separating the
technical descriptions from the conventions of any vendor-specific
piece of hardware.
[0073] In view of the foregoing, the logical operations/functions
set forth in the present technical description are representative
of static or sequenced specifications of various ordered-matter
elements, in order that such specifications may be comprehensible
to the human mind and adaptable to create many various hardware
configurations. The logical operations/functions disclosed herein
should be treated as such, and should not be disparagingly
characterized as abstract ideas merely because the specifications
they represent are presented in a manner that one of skill in the
art can readily understand and apply in a manner independent of a
specific vendor's hardware implementation.
[0074] Referring now to FIG. 1, FIG. 1 illustrates an example
environment 100 in which the methods, systems, circuitry, articles
of manufacture, and computer program products and architecture, in
accordance with various embodiments, may be implemented by personal
device 120. The personal device 120, in various embodiments, may be
endowed with logic that is designed for managing adaptation data,
wherein the adaptation data is correlated to at least one aspect of
speech of a particular party, logic that is designed for
facilitating transmission of the adaptation data to a target
device, wherein the adaptation data is configured to be applied to
the target device to assist in execution of a speech-facilitated
transaction, logic that is designed for facilitating reception of
adaptation result data that is based on at least one aspect of the
speech-facilitated transaction between the particular party and the
target device, logic that is designed for determining whether to
modify the adaptation data at least partly based on the adaptation
result data, and logic that is designed for facilitating
transmission of at least a portion of modified adaptation data to a
receiving device.
[0075] Referring again to the exemplary embodiment 100 of FIG. 1, a
user 5 may engage in a speech-facilitated transaction with a
terminal device 130. Terminal device 130 may include a microphone
122 and a screen 123. In some embodiments, screen 123 may be a
touchscreen. Although FIG. 1A depicts terminal device 130 as a
terminal for simplicity of illustration, terminal device 130 could
be any device that is configured to receive speech. For example,
terminal device 130 may be a terminal, a computer, a navigation
system, a phone, a piece of home electronics (e.g., a DVD player,
Blu-Ray player, media player, game system, television, receiver,
alarm clock, and the like). Terminal device 130 may, in some
embodiments, be a home security system, a safe lock, a door lock, a
kitchen appliance configured to receive speech, and the like. In
some embodiments, terminal device 130 may be a motorized vehicle,
e.g., a car, boat, airplane, motorcycle, golf cart, wheelchair, and
the like. In some embodiments, terminal device 30 may be a piece of
portable electronics, e.g., a laptop computer, a netbook computer,
a tablet device, a smartphone, a cellular phone, a radio, a
portable navigation system, or any other piece of electronics
capable of receiving speech. Terminal device 130 may be a part of
an enterprise solution, e.g., a common workstation in an office, a
copier, a scanner, a personal workstation in a cubicle, an office
directory, an interactive screen, and a telephone. These examples
and lists are not meant to be exhaustive, but merely to illustrate
a few examples of the terminal device.
[0076] In an embodiment, personal device 120 may facilitate the
transmission of adaptation data to the terminal 130. In FIG. 1A,
personal device 120 is shown as a phone-type device that fits into
pocket 15A of the user. Nevertheless, in other embodiments,
personal device 120 may be any size and have any specification.
Personal device 120 may be a custom device of any shape or size,
configured to transmit, receive, and store data. Personal device
120 may include, but is not limited to, a smartphone device, a
tablet device, a personal computer device, a laptop device, a
keychain device, a key, a personal digital assistant device, a
modified memory stick, a universal remote control, or any other
piece of electronics. In addition, personal device 120 may be a
modified object that is worn, e.g., eyeglasses, a wallet, a credit
card, a watch, a chain, or an article of clothing. Anything that is
configured to store, transmit, and receive data may be a personal
device 120, and personal device 120 is not limited in size to
devices that are capable of being carried by a user. Additionally,
personal device 120 may not be in direct proximity to the user,
e.g., personal device 120 may be a computer sitting on a desk in a
user's home or office.
[0077] In some embodiments, terminal device 130 receives adaptation
data from the personal device 120, in a process that will be
described in more detail herein. In some embodiments, personal
device 120 acts as a facilitator, e.g., one that carries out one or
more steps in assisting the transmission, of transmitting
adaptation data to the terminal device 130. For example, as will be
described in more detail herein, personal device 120 may facilitate
transmission of adaptation data from server 110 to terminal device
130. In some embodiments, personal device 120 may generate
adaptation data, as will be described in more detail herein. Thus,
in some embodiments, the adaptation data does not come directly
from the personal device 120. In some embodiments, personal device
120 merely facilitates communication of the adaptation data, e.g.,
by providing one or more of an address, credentials, instructions,
authorization, and recommendations. For example, in some
embodiments, personal device 120 provides a location at server 110
from which adaptation data may be transmitted. In some embodiments,
personal device 120 retrieves adaptation data from server 110 upon
a request from the terminal device 130, and then relays or
facilitates in the relaying of the adaptation data to terminal
device 130.
[0078] In some embodiments, personal device 120 receives adaptation
result data from terminal device 130. In some embodiments, personal
device 120 acts as a facilitator of receiving adaptation result
data at a location. For example, as will be described in more
detail herein, personal device 120 may facilitate reception of
adaptation result data at server 110. In some embodiments, the
adaptation result data 130 may be created by the personal device
120, as will be described in more detail herein. Thus, in some
embodiments, the adaptation result data is not received directly at
the personal device 120. In some embodiments, personal device 120
merely facilitates reception of the adaptation result data, e.g.,
by providing one or more of an address, credentials, instructions,
authorization, and recommendations. For example, in some
embodiments, personal device 120 provides a location at server 110
at which adaptation result data may be received. In some
embodiments, personal device 120 retrieves adaptation result data
from server 110 after facilitating the reception of adaptation
result data from terminal device 130 at server 110.
[0079] In some embodiments, one or more of the adaptation data and
the adaptation result data are transmitted over one or more
communication network(s) 140. In various embodiments, the
communication network 140 may include one or more of a local area
network (LAN), a wide area network (WAN), a metropolitan area
network (MAN), a wireless local area network (WLAN), a personal
area network (PAN), a Worldwide Interoperability for Microwave
Access (WiMAX), public switched telephone network (PTSN), a general
packet radio service (GPRS) network, a cellular network, and so
forth. The communication networks 140 may be wired, wireless, or a
combination of wired and wireless networks. It is noted that
"communication network" here refers to one or more communication
networks, which may or may not interact with each other.
[0080] In some embodiments, personal device 120 broadcasts the
adaptation data regardless of whether a terminal device 130 is
listening, e.g., at predetermined, regular, or otherwise-defined
intervals. In other embodiments, personal device 120 listens for a
request from a terminal device 130, and transmits or broadcasts
adaptation data in response to that request. In some embodiments,
user 105 determines when personal device 120 broadcasts adaptation
data. In still other embodiments, a third party (not shown)
triggers the transmission of adaptation data to the terminal device
130, in which the transmission is facilitated by the personal
device 120.
[0081] Referring again to the exemplary environment 100 depicted in
FIG. 1, in various embodiments, the personal device 120 may
comprise, among other elements, a processor 132, a memory 134, and
a user interface 135. Processor 132 may include one or more
microprocessors, Central Processing Units ("CPU"), a Graphics
Processing Units ("GPU"), Physics Processing Units, Digital Signal
Processors, Network Processors, Floating Point Processors, and the
like. In some embodiments, processor 132 may be a server. In some
embodiments, processor 132 may be a distributed-core processor.
Although processor 132 is depicted as a single processor that is
part of a single computing device 130, in some embodiments,
processor 132 may be multiple processors distributed over one or
many personal devices 120, which may or may not be configured to
work together. Processor 132 is illustrated as being configured to
execute computer readable instructions in order to execute one or
more operations described above, and as illustrated in FIGS. 5,
6A-6H, 7A-7K, and 8A-8J. In some embodiments, processor 132 is
designed to be configured to operate as processing module 150,
which may include adaptation data correlated to at least one
particular party speech aspect managing module 152, adaptation data
configured to be applied to the target device for assistance in
execution of speech-facilitated transaction transmission to target
device when there is an indication of a speech-facilitated
transaction between the target device and the particular party
facilitating module 154, and acquisition of adaptation result data
based on at least one aspect of the speech-facilitated transmission
and configured to be used in determining whether to modify
adaptation data facilitating module 156.
[0082] Referring again to the exemplary environment 100 of FIG. 1,
personal device 120 may comprise a memory 134. In some embodiments,
memory 134 may comprise of one or more of one or more mass storage
devices, read-only memory (ROM), programmable read-only memory
(PROM), erasable programmable read-only memory (EPROM), cache
memory such as random access memory (RAM), flash memory,
synchronous random access memory (SRAM), dynamic random access
memory (DRAM), and/or other types of memory devices. In some
embodiments, memory 134 may be located at a single network site. In
other embodiments, memory 134 may be located at multiple network
sites, including sites that are distant from each other.
[0083] As described above, and with reference to FIG. 1, personal
device 120 may include a user interface 135. The user interface may
be implemented in hardware or software, or both, and may include
various input and output devices to allow an operator of personal
device 120 to interact with personal device 120. For example, user
interface 135 may include, but is not limited to, an audio display,
a video display, a microphone, a camera, a keyboard, a mouse, a
joystick, a game controller, a touchpad, a handset, or any other
device that allows interaction between a computing device and a
user. The user interface 135 also may include a speech interface
136, which is configured to receive and/or process speech as input,
or to observe and/or record speech of a speech-facilitated
transaction.
[0084] Referring again to FIG. 1, in some embodiments, personal
device 120 may have one or more sensors 182. These sensors include,
but are not limited to, a Global Positioning System (GPS) sensor, a
still camera, a video camera, an altimeter, an air quality sensor,
a barometer, an accelerometer, a charge-coupled device, a radio, a
thermometer, a pedometer, a heart monitor, a moisture sensor, a
humidity sensor, a microphone, a seismometer, and a magnetic field
sensor. Sensors 182 may interface with sensor interface 180.
Although FIG. 1B illustrates sensors 182 as part of personal device
120, in some embodiments, sensors 182 may be separated from
personal device 120, and communicate via one or more communication
networks, e.g., communication networks 140.
[0085] Referring now to FIG. 2, FIG. 2 illustrates an exemplary
implementation of the adaptation data correlated to at least one
particular party speech aspect managing module 152. As illustrated
in FIG. 2, the adaptation data correlated to at least one
particular party speech aspect managing module 152 may include one
or more sub-logic modules in various alternative implementations
and embodiments. For example, as shown in FIG. 2 (e.g., FIG. 2A),
in some embodiments, module 152 may include adaptation data
configured to assist in carrying out at least a portion of a
speech-facilitated transaction and correlated to at least one
particular party speech aspect managing module 202. In some
embodiments, module 202 may include adaptation data configured to
adapt a speech recognition component of a target device configured
to carry out a speech-facilitated transaction and correlated to at
least one particular party speech aspect managing module 204. In
some embodiments, module 204 may include adaptation data comprising
a pronunciation dictionary configured to supplement a speech
recognition component of the target device configured to carry out
a speech-facilitated transaction and correlated to at least one
particular party speech aspect managing module 206. In some
embodiments, module 206 may include adaptation data comprising a
pronunciation dictionary configured to supplement a pronunciation
dictionary of the speech recognition component of the target device
configured to carry out a speech-facilitated transaction and
correlated to at least one particular party speech aspect managing
module 208. In some embodiments, module 208 may include adaptation
data comprising a pronunciation dictionary configured to replace at
least one word of a pronunciation dictionary of the speech
recognition component of the target device configured to carry out
a speech-facilitated transaction and correlated to at least one
particular party speech aspect managing module 210. In some
embodiments, module 210 may include adaptation data comprising a
pronunciation dictionary configured to replace at least one word of
a pronunciation dictionary of the speech recognition component of
the target device configured to carry out a speech-facilitated
transaction and based on at least one pronunciation of a word by
the particular party managing module 212.
[0086] Referring again to FIG. 2, e.g., FIG. 2B, in some
embodiments, module 152 may include one or more of adaptation data
correlated to at least one particular party speech aspect storing
module 214, adaptation data correlated to at least one particular
party speech aspect validating at a particular time module 222, and
adaptation data correlated to at least one particular party speech
aspect location information requesting module 224. In some
embodiments, module 214 may include one or more of adaptation data
correlated to at least one particular party speech aspect storing
at remote location module 216 (e.g., which, in some embodiments,
may include adaptation data correlated to at least one particular
party speech aspect storing at remote location that also stores
further adaptation data correlated to a further party module 218)
and address at which adaptation data correlated to at least one
particular party speech aspect is located storing module 220. In
some embodiments, module 224 may include adaptation data correlated
to at least one particular party speech aspect location information
requesting module 224. In some embodiments, module 224 may include
location of adaptation data from list particular party selecting
module 226. In some embodiments, module 226 may include remote data
service center location of adaptation data from list of one or more
remote data service centers particular party selecting module
228.
[0087] Referring again to FIG. 2, e.g., FIG. 2C, in some
embodiments, module 152 may include one or more of adaptation data
correlated to at least one particular party speech aspect
selectively providing viewing authorization module 230 and
adaptation data correlated to at least one particular party speech
aspect selectively providing retrieval authorization module
232.
[0088] Referring now to FIG. 3, FIG. 3 illustrates an exemplary
implementation of the adaptation data transmission to target device
facilitating module 154. As illustrated in FIG. 3, the adaptation
data transmission to target device facilitating module 154 may
include one or more sub-logic modules in various alternative
implementations and embodiments. For example, as shown in FIG. 3
(e.g., FIG. 3A), in some embodiments, module 154 may include one or
more of adaptation data transmitting to target device module 302,
adaptation data retrieval instructions transmission to target
device facilitating module 304, adaptation data retrieval location
transmission to target device facilitating module 306, and
adaptation data representing pronunciation of one or more words in
a particular language spoken by the particular party transmission
to target device facilitating module 308 (e.g., which, in some
embodiments, may include adaptation data representing pronunciation
of one or more words in a particular language spoken by the
particular party that is different from a target-device operation
configured language transmission to target device facilitating
module 310).
[0089] Referring again to FIG. 3, e.g., FIG. 3B, in some
embodiments, module 154 may include one or more of particular
adaptation data selecting from adaptation data module 312 and
particular adaptation data to target device transmission
facilitating module 314. In some embodiments, module 312 may
include one or more of adaptation data from remote location
accessing module 316, particular adaptation data selecting from
accessed adaptation data module 318, and particular adaptation data
from accessed adaptation data retrieving module 320. In some
embodiments, module 312 may further include particular adaptation
data selecting based on at least one target device property module
322. In some embodiments, module 322 may include subset of
adaptation data selecting based on at least one target device
property module 324. In some embodiments, module 324 may include
portion of inflection database selecting based on at least one
target device property module 326. In some embodiments, module 326
may include portion of inflection database selecting based on one
or more words associated with target device module 328. In some
embodiments, module 328 may include portion of inflection database
selecting based on one or more words associated with an automated
teller device module 330. In some embodiments, module 330 may
include portion of inflection database selecting based on words
related to money determined to be associated with an automated
teller device module 332.
[0090] Referring again to FIG. 3, e.g., FIG. 3C, in some
embodiments, module 154 may include module 312, and module 312 may
include module 322, as previously described above. In some
embodiments, module 322 may further include one or more of
information regarding the at least one property of the target
device receiving from target device module 334, particular
adaptation data selecting based on at least the received property
of the target device module 336, and particular adaptation data
selecting based on a target device mode module 344. In some
embodiments, module 334 may include information regarding at least
one word commonly used as a target device command receiving from
target device module 338. In some embodiments, module 338 may
include information regarding at least one word commonly used to
command a digital video disc player command receiving from the
digital video disc player module 340. In some embodiments, module
340 may include command play as a word commonly used to command a
digital video disc player receiving from the digital video disc
player module 342.
[0091] Referring again to FIG. 3, e.g., FIG. 3D, in some
embodiments, module 154 may include module 312, and module 312 may
include module 322, as previously described above. In some
embodiments, module 322 may still further include particular
adaptation data selecting based on a type of target device module
346. In some embodiments, module 346 may include subset of
adaptation data derived at least in part from one or more devices
of a same type as the target device selecting module 348. In some
embodiments, module 348 may include subset of adaptation data
derived at least in part from one or more speech interactions with
one or more devices of a same type as the target device selecting
module 350. In some embodiments, module 350 may include one or more
of subset of adaptation data derived at least in part from one or
more speech interactions with home entertainment devices when the
target device is a voice input accepting television selecting
module 352 and subset of adaptation data derived at least in part
from one or more speech interactions with one or more televisions
when the target device is a voice input accepting television
selecting module 354.
[0092] Referring again to FIG. 3, e.g., FIG. 3E, in some
embodiments, module 154 may include module 312, and module 312 may
include module 322, as previously described above. In some
embodiments, module 322 may still further include one or more of
particular adaptation data selecting based on a speech receiving
component of target device module 356 and particular adaptation
data selecting based on at least one motor vehicle property module
362. In some embodiments, module 356 may include one or more of
particular adaptation data selecting based on a quality of a
microphone of target device module 358 and particular adaptation
data selecting based on a type of a microphone of target device
module 360. In some embodiments, module 362 may include one or more
of particular adaptation data selecting based on motor vehicle
velocity module 364 and particular adaptation data selecting based
on motor vehicle vibration level module 366.
[0093] Referring again to FIG. 3, e.g., FIG. 3F, in some
embodiments, module 154 may include module 312, as previously
described above. In some embodiments, module 312 may further
include one or more of particular adaptation data selecting based
on an environment condition of an environment of the
speech-facilitated transaction module 368 (e.g., which, in some
embodiments, may include one or more of particular adaptation data
selecting based on an ambient noise level of an environment of the
speech-facilitated transaction module 370, particular adaptation
data selecting based on a distance between the particular party and
the target device during the speech-facilitated transaction module
372, and particular adaptation data selecting based on an amount of
interference present in an environment of the speech-facilitated
transaction module 374), selection of particular adaptation data
from particular party receiving module 376, adaptation data
presenting to particular party for selection of particular
adaptation data module 378, and selection of particular adaptation
data from the particular party receiving module 380.
[0094] Referring again to FIG. 3, e.g., FIG. 3G, in some
embodiments, module 154 may include module 312, as previously
described above. In some embodiments, module 312 may still further
include one or more of selection of particular adaptation data
based on previously acquired user preferences module 382,
transmitting options for selecting adaptation data to target device
module 384, target device selection of adaptation data receiving
module 386, and particular adaptation data selection based on
received adaptation data selected by target device module 388. In
some embodiments, module 154 may include particular
party-correlated adaptation data receiving facilitated by
particular party associated particular device upon indication from
target device of initiation of speech-facilitated transaction
between target device and particular party module 390.
[0095] Referring now to FIG. 4, FIG. 4 illustrates an exemplary
implementation of the adaptation result data based on a result of
at least one aspect of a speech-facilitated transaction reception
facilitating module 156. As illustrated in FIG. 4, the adaptation
result data based on a result of at least one aspect of a
speech-facilitated transaction reception facilitating module 156
may include one or more sub-logic modules in various alternative
implementations and embodiments. For example, as shown in FIG. 4
(e.g., FIG. 4A), in some embodiments, module 156 may include one or
more of adaptation result data based on a result of at least one
aspect of a speech-facilitated transaction reception at a location
assisting module 402, adaptation result data based on a result of
at least one aspect of a speech-facilitated transaction receiving
module 404, address of location configured to receive adaptation
result data based on a result of at least one aspect of a
speech-facilitated transaction providing module 406, and address of
location configured to receive adaptation result data based on a
result of at least one aspect of a speech-facilitated transaction
receiving module 408.
[0096] Referring again to FIG. 4, e.g., FIG. 4B, in some
embodiments, module 156 may include adaptation result data based on
a result of the speech-facilitated transaction reception
facilitating module 410. In some embodiments, module 410 may
include adaptation result data based on a measure of success of the
speech-facilitated transaction reception facilitating module 412.
In some embodiments, module 412 may include adaptation result data
comprising a representation of success of the speech-facilitated
transaction reception facilitating module 414. In some embodiments,
module 414 may include one or more of adaptation result data
comprising a particular party provided representation of success of
the speech-facilitated transaction reception facilitating module
416, adaptation result data comprising a target device provided
representation of success of the speech-facilitated transaction
reception facilitating module 418, and adaptation result data
comprising a non-numeric representation of success of the
speech-facilitated transaction reception facilitating module
420.
[0097] Referring again to FIG. 4, e.g., FIG. 4C, in some
embodiments, module 156 may include module 410, module 410 may
include module 412, and module 412 may include module 414, as
previously described above. In some embodiments, module 414 may
further include one or more of adaptation result data comprising a
numeric representation of success of the speech-facilitated
transaction reception facilitating module 422 (e.g., which, in some
embodiments, may include one or more of adaptation result data
comprising a confidence rate of correct interpretation of at least
a portion of the speech-facilitated transaction reception
facilitating module 424 and adaptation result data comprising an
interpretation error rate of at least a portion of the
speech-facilitated transaction reception facilitating module 426)
and adaptation result data comprising a list of at least one word
improperly interpreted during speech-facilitated transaction
reception facilitating module 428.
[0098] Referring again to FIG. 4, e.g., FIG. 4D, in some
embodiments, module 156 may include one or more of adaptation
result data comprising a list of at least one word improperly
interpreted more than once during the speech-facilitated
transaction reception facilitating module 430, adaptation result
data comprising a table of at least one word improperly interpreted
and a number of times the at least one word was improperly
interpreted during the speech-facilitated transaction reception
facilitating module 432, adaptation result data comprising a list
of at least one question asked by the target device at least twice
consecutively reception facilitating module 434, adaptation result
data comprising a list of at least one question asked by the target
device at least twice consecutively and one or more answers given
to the at least one question reception facilitating module 436, and
adaptation result data comprising a table of at least one question
asked by the target device and at least one corresponding answer
given by the particular party reception facilitating module
438.
[0099] Referring again to FIG. 4, e.g., FIG. 4E, in some
embodiments, module 156 may include one or more of adaptation
result data comprising at least one phoneme appearing in at least
one word that was improperly interpreted during the
speech-facilitated transaction reception facilitating module 440
(e.g., which, in some embodiments, may include adaptation result
data comprising at least one phoneme appearing in more than one
word that was improperly interpreted during the speech-facilitated
transaction reception facilitating module 442 (e.g., which, in some
embodiments, may include adaptation result data comprising at least
one phoneme appearing in more than one unique word that was
improperly interpreted during the speech-facilitated transaction
reception facilitating module 444)), adaptation result data based
on a result of at least one aspect of a speech-facilitated
transaction reception facilitating upon conclusion of
speech-facilitated transaction module 446, determining a conclusion
of a speech facilitated transaction based on facilitating reception
of adaptation result data module 448, adaptation result data based
on a result of at least one aspect of a speech-facilitated
transaction reception facilitating during speech-facilitated
transaction module 450, and adaptation result data based on a
result of at least one aspect of a speech-facilitated transaction
reception facilitating prior to completing the speech-facilitated
transaction module 452.
[0100] Referring now to FIG. 5, FIG. 5 illustrates an exemplary
implementation of the adaptation data modification determining at
least partly based on adaptation result data module 158. As
illustrated in FIG. 5, the adaptation data modification determining
at least partly based on adaptation result data module 158 may
include one or more sub-logic modules in various alternative
implementations and embodiments. For example, as shown in FIG. 5
(e.g., FIG. 5A), in some embodiments, module 158 may include one or
more of adaptation data modification instructions at least partly
based on adaptation result data receiving module 502,
speech-facilitated transaction between target device and particular
party monitoring module 504, and modification of adaptation data
determining based on adaptation result data indication of success
below threshold level module 506. In some embodiments, module 506
may include, e.g., modification of adaptation data determining
based on threshold level of success rate of speech-facilitated
transaction module 508. In some embodiments, module 508 may include
modification of adaptation data determining based on a number of
words improperly interpreted during speech-facilitated transaction
below a threshold level module 510.
[0101] Referring again to FIG. 5, e.g., FIG. 5B, module 158 may
include adaptation data modifying at least partly based on
adaptation result data module 512. In some embodiments, module 512
may include pronunciation dictionary modifying at least one word at
least partly based on received adaptation result data comprising at
least one word that was improperly interpreted and a pronunciation
of the at least one word by the particular party module 514. In
some embodiments, module 514 may include pronunciation dictionary
replacing at least one word received in adaptation result data with
pronunciation received as adaptation data module 516.
[0102] Referring now to FIG. 6, FIG. 6 illustrates an exemplary
implementation of the at least a portion of modified adaptation
data transmission to receiving device facilitating module 160. As
illustrated in FIG. 6, the at least a portion of modified
adaptation data transmission to receiving device facilitating
module 160 may include one or more sub-logic modules in various
alternative implementations and embodiments. For example, as shown
in FIG. 6 (e.g., FIG. 6A), in some embodiments, module 160 may
include one or more of at least a portion of a voice sample
received as a portion of the adaptation result data transmission to
receiving device facilitating module 602, at least a portion of
modified adaptation data transmission to target device as receiving
device facilitating module 604 (e.g., which, in some embodiments,
may include one or more of at least a portion of modified
adaptation data transmission prior to completion of
speech-facilitated transaction facilitating module 606, at least a
portion of modified adaptation data transmission to receiving
device during speech facilitated transaction facilitating module
608, at least a portion of modified adaptation data configured to
be received prior to completion of speech-facilitated transaction
transmission facilitating module 610, and at least a portion of
modified adaptation data configured to be applied prior to
completion of speech-facilitated transaction transmission
facilitating module 612), and at least a portion of modified
adaptation data transmission to device other than the target device
facilitating module 614.
[0103] Referring again to FIG. 6, e.g., FIG. 6B, module 160 may
include one or more of at least a portion of modified adaptation
data transmission to a device that is a replacement for the target
device facilitating module 616, at least a portion of modified
adaptation data transmission to receiving device connected to the
target device via a network facilitating module 618, at least a
portion of modified adaptation data transmission to receiving
device communicating on a same network as the target device
facilitating module 620, at least a portion of modified adaptation
data transmission to receiving device configured to perform a same
function as the target device facilitating module 622, and at least
a portion of modified adaptation data transmission to receiving
device of a same type as the target device facilitating module
624.
[0104] Referring again to FIG. 6, e.g., FIG. 6C, module 160 may
include one or more of modified adaptation data transmitting from
particular device to receiving device module 626 (e.g., which, in
some embodiments, may include modified adaptation data transmitting
from particular device configured to communicate on a same network
as the receiving device module 628, modified adaptation data
transmitting from particular device configured to communicate with
receiving device and target device module 630, and modified
adaptation data stored on particular device transmitting from
particular device to receiving device module 632), adaptation data,
said adaptation data modified by incrementing a counter, as at
least a portion of modified adaptation data transmission to
receiving device facilitating module 634, at least a portion of
modified adaptation data, said modified adaptation data different
than the adaptation data, transmission to receiving device
facilitating module 636, and at least a portion of modified
adaptation data based on the adaptation data transmission to
receiving device facilitating module 638.
[0105] Referring again to FIG. 6, e.g., FIG. 6D, module 160 may
include one or more of at least a portion of modified adaptation
data, said modified adaptation data including at least a portion of
the adaptation result data, transmission to receiving device
facilitating module 640 and at least a portion of modified
adaptation data, said modified adaptation data at least partially
based on applying the adaptation result data, transmission to
receiving device facilitating module 642.
[0106] A more detailed discussion related to terminal device 30 of
FIG. 1 now will be provided with respect to the processes and
operations to be described herein. Referring now to FIG. 6, FIG. 7
illustrates an operational flow 700 representing example operations
for, among other methods, managing adaptation data, wherein the
adaptation data is correlated to at least one aspect of speech of a
particular party, facilitating transmission of the adaptation data
to a target device, wherein the adaptation data is configured to be
applied to the target device to assist in execution of a
speech-facilitated transaction, facilitating reception of
adaptation result data that is based on at least one aspect of the
speech-facilitated transaction between the particular party and the
target device, determining whether to modify the adaptation data at
least partly based on the adaptation result data, and facilitating
transmission of at least a portion of modified adaptation data to a
receiving device.
[0107] In FIG. 7 and in the following FIGS. 8-12 that include
various examples of operational flows, discussions and explanations
will be provided with respect to the exemplary environment 100 as
described above and as illustrated in FIG. 1, and with respect to
other examples (e.g., as provided in FIGS. 2-6) and contexts. It
should be understood that the operational flows may be executed in
a number of other environments and contexts, and/or in modified
versions of the systems shown in FIGS. 2-6. Although the various
operational flows are presented in the sequence(s) illustrated, it
should be understood that the various operations may be performed
in other orders other than those which are illustrated, or may be
performed concurrently.
[0108] In some implementations described herein, logic and similar
implementations may include software or other control structures.
Electronic circuitry, for example, may have one or more paths of
electrical current constructed and arranged to implement various
functions as described herein. In some implementations, one or more
media may be configured to bear a device-detectable implementation
when such media hold or transmit device detectable instructions
operable to perform as described herein. In some variants, for
example, implementations may include an update or modification of
existing software or firmware, or of gate arrays or programmable
hardware, such as by performing a reception of or a transmission of
one or more instructions in relation to one or more operations
described herein. Alternatively or additionally, in some variants,
an implementation may include special-purpose hardware, software,
firmware components, and/or general-purpose components executing or
otherwise invoking special-purpose components. Specifications or
other implementations may be transmitted by one or more instances
of tangible transmission media as described herein, optionally by
packet transmission or otherwise by passing through distributed
media at various times.
[0109] Those having skill in the art will recognize that the state
of the art has progressed to the point where there is little
distinction left between hardware, software, and/or firmware
implementations of aspects of systems; the use of hardware,
software, and/or firmware is generally (but not always, in that in
certain contexts the choice between hardware and software can
become significant) a design choice representing cost vs.
efficiency tradeoffs. Those having skill in the art will appreciate
that there are various vehicles by which processes and/or systems
and/or other technologies described herein can be effected (e.g.,
hardware, software, and/or firmware), and that the preferred
vehicle will vary with the context in which the processes and/or
systems and/or other technologies are deployed. For example, if an
implementer determines that speed and accuracy are paramount, the
implementer may opt for a mainly hardware and/or firmware vehicle;
alternatively, if flexibility is paramount, the implementer may opt
for a mainly software implementation; or, yet again alternatively,
the implementer may opt for some combination of hardware, software,
and/or firmware. Hence, there are several possible vehicles by
which the processes and/or devices and/or other technologies
described herein may be effected, none of which is inherently
superior to the other in that any vehicle to be utilized is a
choice dependent upon the context in which the vehicle will be
deployed and the specific concerns (e.g., speed, flexibility, or
predictability) of the implementer, any of which may vary. Those
skilled in the art will recognize that optical aspects of
implementations will typically employ optically-oriented hardware,
software, and or firmware.
[0110] Throughout this application, examples and lists are given,
with parentheses, the abbreviation "e.g.," or both. Unless
explicitly otherwise stated, these examples and lists are merely
exemplary and are non-exhaustive. In most cases, it would be
prohibitive to list every example and every combination. Thus,
smaller, illustrative lists and examples are used, with focus on
imparting understanding of the claim terms rather than limiting the
scope of such terms.
[0111] Portions of this application may reference trademarked
companies and products merely for exemplary purposes. All
trademarks remain the sole property of the trademark owner, and in
each case where a trademarked product or company is used, a similar
product or company may be replaced.
[0112] The following examples are meant to be non-exhaustive
illustrations of a few of the many embodiments disclosed in the
invention. Descriptive statements or other statements that define,
limit, or further elaborate upon the function, operation,
execution, or implementation of the following examples are intended
to apply in the context of the described exemplary embodiment, and
are intended to show that said examples could be applied to any
other embodiment when not inconsistent with other explicit
descriptions, but should not be interpreted as limiting any other
embodiment, whether explicitly listed or implicitly encompassed by
the scope of the invention set forth in the foregoing claims.
[0113] Following are a series of flowcharts depicting
implementations. For ease of understanding, the flowcharts are
organized such that the initial flowcharts present implementations
via an example implementation and thereafter the following
flowcharts present alternate implementations and/or expansions of
the initial flowchart(s) as either sub-component operations or
additional component operations building on one or more
earlier-presented flowcharts. Those having skill in the art will
appreciate that the style of presentation utilized herein (e.g.,
beginning with a presentation of a flowchart(s) presenting an
example implementation and thereafter providing additions to and/or
further details in subsequent flowcharts) generally allows for a
rapid and easy understanding of the various process
implementations. In addition, those skilled in the art will further
appreciate that the style of presentation used herein also lends
itself well to modular and/or object-oriented program design
paradigms.
[0114] Further, in FIG. 7 and in the figures to follow thereafter,
various operations may be depicted in a box-within-a-box manner.
Such depictions may indicate that an operation in an internal box
may comprise an optional example embodiment of the operational step
illustrated in one or more external boxes. However, it should be
understood that internal box operations may be viewed as
independent operations separate from any associated external boxes
and may be performed in any sequence with respect to all other
illustrated operations, or may be performed concurrently. Still
further, these operations illustrated in FIG. 7 as well as the
other operations to be described herein may be performed by at
least one of a machine, an article of manufacture, or a composition
of matter.
[0115] Referring again to FIG. 7, FIG. 7 shows operation 700 that
includes operation 702 depicting managing adaptation data, wherein
the adaptation data is correlated to at least one aspect of speech
of a particular party. For example, FIG. 1 (e.g., FIG. 1B) shows
adaptation data correlated to at least one particular party speech
aspect managing module 152 managing (e.g., storing, tracking,
monitoring, authorizing, changing the permissions of, providing
access, allocating storage for, retrieving, receiving, processing,
altering, comparing, or otherwise performing one or more operations
on) adaptation data (e.g., instructions for replacing a word
frequency table with a modified word frequency table that reflects
the particular party's word usage), wherein the adaptation data
(e.g., the instructions for replacing a word frequency table with a
modified word frequency table that reflects the particular party's
word usage) is correlated to at least one aspect of speech (e.g.,
how often one or more particular words are used) of a particular
party (e.g., a user of an automated teller machine device
terminal).
[0116] Referring again to FIG. 7, operation 700 may include
operation 704 depicting facilitating transmission of the adaptation
data to a target device, wherein the adaptation data is configured
to be applied to the target device to assist in execution of a
speech-facilitated transaction. For example, FIG. 1 (e.g., FIG. 1B)
shows adaptation data transmission to target device facilitating
module 154 facilitating transmission (e.g., transmitting, or taking
one or more steps that will assist in the transmission of,
regardless of the starting or ending point) of the adaptation data
(e.g., the instructions for replacing a word frequency table with a
modified word frequency table that reflects the particular party's
word usage) to a target device (e.g., a device the particular
party, e.g., the user is interacting with, e.g., the user of an
automated teller machine device terminal), wherein the adaptation
data (e.g., the instructions for replacing a word frequency table
with a modified word frequency table that reflects the particular
party's word usage) is configured to be applied (e.g., the
adaptation data can be applied, with various levels of processing
ranging from "none at all," to "substantial amounts of processing")
to the target device (e.g., the automated teller machine device
terminal) to assist in execution (e.g., to be used in at least one
operation that will or could be carried out) of a
speech-facilitated transaction (e.g., withdrawing two hundred
dollars from the automated teller machine device terminal by
commanding the automated teller machine device using speech
commands for at least part of the transaction).
[0117] Referring again to FIG. 7, operation 700 may include
operation 706 depicting facilitating reception of adaptation result
data that is based on at least one aspect of the speech-facilitated
transaction between the particular party and the target device. For
example, FIG. 1 shows adaptation result data based on a result of
at least one aspect of a speech-facilitated transaction reception
facilitating module 156 facilitating reception (e.g., receiving, or
taking one or more steps that will assist in the reception of)
adaptation result data (e.g., a periodically-updated interpretation
error rate that represents a rate at which words spoken by the user
are not interpreted correctly by the automated teller machine
device terminal) that is based on at least one aspect (e.g.,
correct interpretation of one or more words of) the
speech-facilitated transaction (e.g., the withdrawing two hundred
dollars from the automated teller machine device terminal) between
the particular party (e.g., the user withdrawing the money) and the
target device (e.g., the automated teller machine device
terminal).
[0118] Referring again to FIG. 7, operation 700 may include
operation 708 depicting determining whether to modify the
adaptation data at least partly based on the adaptation result
data. For example, FIG. 1 shows adaptation data modification
determining at least partly based on adaptation result data module
158 determining whether to modify the adaptation data (e.g., the
instructions for replacing a word frequency table with a modified
word frequency table that reflects the particular party's word
usage) at least partly based on the adaptation result data (e.g., a
periodically-updated interpretation error rate that represents a
rate at which words spoken by the user are not interpreted
correctly by the automated teller machine device terminal, and when
that rate goes above a certain percent, then the values in the word
frequency table may be adjusted based on other data, whether
collected from the particular party or not, in order to more
accurately predict the words that were spoken, particularly within
context, with the goal of decreasing the interpretation error rate
by shifting the percentages when a speech recognition component of
the automated teller machine device terminal is trying to interpret
one or more words that the user is speaking).
[0119] Referring again to FIG. 7, operation 700 may include
operation 710 depicting facilitating transmission of at least a
portion of modified adaptation data to a receiving device. For
example, FIG. 1 shows at least a portion of modified adaptation
data transmission to receiving device facilitating module 160
facilitating transmission (e.g., transmitting, or taking one or
more steps that will assist in the transmission of, regardless of
the starting or ending point) of at least a portion of modified
adaptation data (e.g., part or all of the modified word frequency
table that reflects the particular party's word usage and that has
been modified) to a receiving device (e.g., in an embodiment, the
modification takes place prior to conclusion of the
speech-facilitated transaction, and the modified adaptation data is
sent back to the same automated teller machine device terminal). In
some embodiments, the receiving device is different than the target
device, as will be described in more detail herein.
[0120] FIGS. 8A-8P depict various implementations of operation 702,
according to embodiments. Referring now to FIG. 8A, operation 702
may include operation 802 depicting managing data configured to
assist in carrying out at least a portion of a speech transaction
conducted by the particular party, wherein the adaptation data is
correlated to at least one aspect of speech of the particular
party. For example, FIG. 2 shows adaptation data configured to
assist in carrying out at least a portion of a speech-facilitated
transaction and correlated to at least one particular party speech
aspect managing module 202 managing data (e.g., a list of the way
that the particular party pronounces ten words, e.g., the numbers
zero through nine) configured to assist in carrying out (e.g., the
data will be used to improve accuracy of the component processing
the user's speech, specifically when processing spoken numbers,
e.g., "three cheeseburgers") at least a portion of a speech
transaction (e.g., ordering a cheeseburger from an automated
drive-thru window) conducted by the particular party (e.g., the
customer ordering from his car), wherein the adaptation data (e.g.
the list of the way that the particular party pronounces the ten
words) is correlated to at least one aspect of speech (e.g.,
pronunciation) of the particular party (e.g., the customer ordering
from his car).
[0121] Referring again to FIG. 8A, operation 802 may include
operation 804 depicting managing data comprising instructions for
adapting a speech recognition component of a target device
configured to carry out at least a portion of the speech
transaction conducted by the particular party, wherein the
adaptation data is correlated to at least one aspect of speech of
the particular party. For example, FIG. 2 shows adaptation data
configured to adapt a speech recognition component of a target
device configured to carry out a speech-facilitated transaction and
correlated to at least one particular party speech aspect managing
module 204 managing data comprising instructions for adapting a
speech recognition component (e.g., the hardware or software inside
an automated airline ticket dispenser that processes speech) of a
target device (e.g., the automated airline ticket dispenser)
configured to carry out at least a portion of the speech
transaction (e.g., printing the airline ticket) conducted by the
particular party (e.g., the prospective passenger), wherein the
adaptation data (e.g., instructions for replacing a word frequency
table with a modified word frequency table that reflects the
particular party's word usage, e.g., the particular party may be
from Washington, D.C., and thus the words "D.C." might have a
higher usage than the standard for the automated airline ticket
dispenser), is correlated to at least one aspect of speech (e.g.,
frequency of word usage) of the particular party.
[0122] Referring again to FIG. 8A, operation 804 may include
operation 806 depicting managing data comprising a pronunciation
dictionary that is configured to supplement a speech recognition
component of the target device configured to carry out at least a
portion of the speech transaction conducted by the particular
party, wherein the adaptation data is correlated to at least one
aspect of speech of the particular party. For example, FIG. 2 shows
adaptation data comprising a pronunciation dictionary configured to
supplement a speech recognition component of the target device
configured to carry out a speech-facilitated transaction and
correlated to at least one particular party speech aspect managing
module 206 managing data comprising a pronunciation dictionary that
is configured to supplement a speech recognition component (e.g.,
the speech recognition and processing module) of the target device
(e.g., a speech-enabled Blu-ray player) configured to carry out at
least a portion of the speech transaction (e.g., ordering the
device to play a particular episode of "The Wire Season 4" disc)
conducted by the particular party (e.g., the user and/or owner of
the Blu-ray device), wherein the adaptation data is correlated to
at least one aspect of speech (e.g., pronunciation) of the
particular party.
[0123] Referring again to FIG. 8A, operation 806 may include
operation 808 depicting managing data comprising a pronunciation
dictionary that is configured to supplement a pronunciation
dictionary of the speech recognition module of the target device
configured to carry out at least a portion of the
speech-facilitated transaction conducted by the particular party,
wherein the adaptation data is correlated to at least one aspect of
speech of the particular party. For example, FIG. 2 shows
adaptation data comprising a pronunciation dictionary configured to
supplement a pronunciation dictionary of the speech recognition
component of the target device configured to carry out a
speech-facilitated transaction and correlated to at least one
particular party speech aspect managing module 208 managing data
comprising a pronunciation dictionary that is configured to
supplement a pronunciation dictionary of the speech recognition
module of the target device (e.g., a portable, car-mountable
navigation system, e.g., Garmin Nuvi, that can receive speech
commands) configured to carry out at least a portion of the
speech-facilitated transaction (e.g., asking for directions to the
nearest Five Guys burgers) conducted by the particular party (e.g.,
the user of the device), wherein the adaptation data is correlated
to at least one aspect of speech (e.g., pronunciation) of the
particular party.
[0124] Referring again to FIG. 8A, operation 808 may include
operation 810 depicting managing data comprising a pronunciation
dictionary that is configured to replace at least one word of a
speech recognition component pronunciation dictionary of the target
device configured to carry out at least a portion of the
speech-facilitated transaction conducted by the particular party,
wherein the adaptation data is correlated to at least one aspect of
speech of the particular party. For example, FIG. 2 shows
adaptation data comprising a pronunciation dictionary configured to
replace at least one word of a pronunciation dictionary of the
speech recognition component of the target device configured to
carry out a speech-facilitated transaction and correlated to at
least one particular party speech aspect managing module 210
managing data comprising a pronunciation dictionary that is
configured to replace at least one word (e.g., "run faster") of a
speech recognition component pronunciation dictionary of the target
device (e.g., a video game system) configured to carry out at least
a portion of the speech-facilitated transaction (e.g., issuing a
command to the game) conducted by the particular party (e.g., the
video game player), wherein the adaptation data (e.g., the
pronunciation dictionary) is correlated to at least one aspect of
speech (e.g., pronunciation) of the particular party (e.g., the
video game player).
[0125] Referring now to FIG. 8B, operation 810 may include
operation 812 depicting managing data comprising a pronunciation
dictionary that is configured to supplement the speech recognition
component pronunciation dictionary of the target device configured
to carry out at least a portion of the speech transaction conducted
by the particular party, wherein the pronunciation dictionary is
based on pronunciation of one or more words by the particular
party. For example, FIG. 2 shows adaptation data comprising a
pronunciation dictionary configured to replace at least one word of
a pronunciation dictionary of the speech recognition component of
the target device configured to carry out a speech-facilitated
transaction and based on at least one pronunciation of a word by
the particular party managing module 212 managing data comprising a
pronunciation dictionary that is configured to supplement the
speech recognition component pronunciation dictionary of the target
device (e.g., a smartphone configured to receive voice commands)
configured to carry out at least a portion of the speech
transaction (e.g., ordering the smartphone to make a call)
conducted by the particular party (e.g., the user), wherein the
pronunciation dictionary is based on pronunciation of one or more
words by the particular party (e.g., "call," "home," "pizza
parlor").
[0126] Referring now to FIG. 8C, operation 702 may include
operation 814 depicting storing adaptation data, wherein the
adaptation data is correlated to at least one aspect of speech of
the particular party. For example, FIG. 2 shows adaptation data
correlated to at least one particular party speech aspect storing
module 214 storing (e.g., placing, writing, moving, or accepting
into memory) adaptation data (e.g., a phoneme pronunciation
database), wherein the adaptation data (e.g., the phoneme
pronunciation database) is correlated to at least one aspect of
speech of the particular party (e.g., the phoneme pronunciation
database is keyed to the particular party's pronunciation of
phonemes).
[0127] Referring again to FIG. 8C, operation 814 may include
operation 816 depicting storing adaptation data at a remote
location, wherein the adaptation data is correlated to at least one
aspect of speech of the particular party. For example, FIG. 2 shows
adaptation data correlated to at least one particular party speech
aspect storing at remote location module 216 storing adaptation
data (e.g., a phrase completion algorithm) at a remote location
(e.g., a computer, server, or other device that is discrete from
the particular device carrying out one or more of the steps),
wherein the adaptation data is correlated to at least one aspect of
speech of the particular party (e.g., the phrase completion
algorithm is at least partly based on the previous speech of the
user).
[0128] Referring again to FIG. 8C, operation 816 may include
operation 818 depicting storing adaptation data at a remote
location at which further adaptation data for at least one further
party is also stored, wherein the adaptation data is correlated to
at least one aspect of speech of the particular party. For example,
FIG. 2, e.g., FIG. 2B, shows adaptation data correlated to at least
one particular party speech aspect storing at remote location that
also stores further adaptation data correlated to a further party
module 218 storing adaptation data (e.g., a basic pronunciation
adjustment algorithm) at a remote location (e.g., a remote server)
at which further adaptation data (e.g., one or more other basic
pronunciation adjustment algorithms at least partly based on
previous speech of one or more parties other than the particular
party) for at least one further party (e.g., someone other than the
user) is also stored, wherein the adaptation data is correlated to
at least one aspect of speech of the particular party (e.g., the
basic pronunciation adjustment algorithm is based on the user's
speech).
[0129] Referring again to FIG. 8C, operation 814 may include
operation 820 depicting storing an address at which the adaptation
data is stored, wherein the adaptation data is correlated to at
least one aspect of speech of a particular party. For example, FIG.
2, e.g., FIG. 2B, shows address at which adaptation data correlated
to at least one particular party speech aspect is located storing
module 220 storing an address (e.g., a location, e.g., a web
address, or an address in memory) at which the adaptation data
(e.g., a French language substitution algorithm) is stored, wherein
the adaptation data is correlated to at least one aspect of speech
of a particular party (e.g., the particular party is a French
speaker, and the adaptation data replaces the English
pronunciations of words with their French counterparts).
[0130] Referring again to FIG. 8C, operation 702 may include
operation 822 depicting validating the adaptation data at one or
more particular times. For example, FIG. 2, e.g., FIG. 2B, shows
adaptation data correlated to at least one particular party speech
aspect validating at a particular time module 222 validating (e.g.,
determining that the adaptation data is valid, e.g., by measuring
the size, or by generating a hash based on the data for comparison)
the adaptation data (e.g., an utterance ignoring algorithm) at one
or more particular times (e.g., once a day).
[0131] Referring again to FIG. 8C, operation 702 may include
operation 824 depicting requesting information regarding a location
of the adaptation data from the particular party. For example, FIG.
2, e.g., FIG. 2B, shows adaptation data correlated to at least one
particular party speech aspect location information requesting
module 224 requesting information regarding a location of the
adaptation data (e.g., requesting to know an IP or World Wide Web
address of the location of the adaptation data, e.g., through
prompting, either with speech or through some other interface) from
the particular party (e.g., the user).
[0132] Referring again to FIG. 8C, operation 824 may include
operation 826 depicting requesting that the particular party select
a location of the adaptation data from a list of one or more
locations. For example, FIG. 2, e.g., FIG. 2B, shows location of
adaptation data from list particular party selecting module 226
requesting that the particular party (e.g., the user) select a
location of the adaptation data (e.g., a country where the user is
located, which is also the location of the closest server where the
adaptation data may be found, even though the adaptation data may
also be in other locations) from a list of one or more locations
(e.g., countries that house servers that store adaptation
data).
[0133] Referring again to FIG. 8C, operation 826 may include
operation 828 depicting requesting that the particular party select
a remote data service center at which the adaptation data is
located from a list of one or more remote data service centers. For
example, FIG. 2, e.g., FIG. 2B, shows remote data service center
location of adaptation data from list of one or more remote data
service centers particular party selecting module 228 requesting
that the particular party (e.g., the user) select a remote data
service center (e.g., a cloud service provided by, e.g., Google, or
Amazon, or Microsoft, or another remote data center provider) at
which the adaptation data is located, from a list of one or more
remote data service centers (e.g., the various remote data service
centers are listed for selection by the user through any of a
variety of interfaces).
[0134] Referring now to FIG. 8D, operation 702 may include
operation 830 depicting selectively providing authorization to view
the adaptation data. For example, FIG. 2, e.g., FIG. 2C, shows
adaptation data correlated to at least one particular party speech
aspect selectively providing viewing authorization module 230
selectively providing authorization (e.g., providing a limited-use
password, a time-based password, or other type of password) to view
(e.g., use, and to transmit data for use with the adaptation data,
but without retrieving a local copy of the adaptation data) the
adaptation data (e.g., a noise level dependent filtration
algorithm).
[0135] Referring again to FIG. 8D, operation 702 may include
operation 832 depicting selectively providing authorization to
retrieve the adaptation data. For example, FIG. 2, e.g., FIG. 2C,
shows adaptation data correlated to at least one particular party
speech aspect selectively providing retrieval authorization module
232 selectively providing authorization (e.g., a one-time retrieval
code) to retrieve (e.g. copy from a different location) the
adaptation data (e.g., an emotion-based pronunciation adjustment
algorithm for use when the particular party is speaking under
duress, e.g., after a car accident, and the particular party is
speaking to the car's automated systems).
[0136] FIGS. 9A-9G depict various implementations of operation 704,
according to embodiments. Referring now to FIG. 9A, operation 704
may include operation 902 depicting transmitting the adaptation
data to the target device, wherein the adaptation data is
configured to be applied to the target device to assist in
execution of the speech-facilitated transaction. For example, FIG.
3, e.g., FIG. 3A, shows adaptation data transmitting to target
device module 302 transmitting the adaptation data (e.g., a
syllable pronunciation database) to the target device (e.g., the
in-vehicle entertainment system), wherein the adaptation data
(e.g., the syllable pronunciation database) is configured to be
applied to the target device (e.g., the in-vehicle entertainment
system) to assist in execution of the speech-facilitated
transaction (e.g., raising the volume).
[0137] Referring again to FIG. 9A, operation 704 may include
operation 904 depicting transmitting instructions for retrieving
the adaptation data to the target device, wherein the adaptation
data is configured to be applied to the target device to assist in
execution of the speech-facilitated transaction. For example, FIG.
3, e.g., FIG. 3A, shows adaptation data retrieval instructions
transmission to target device facilitating module 304 transmitting
instructions (e.g., a list of passwords needed, or an address where
the information can be accessed) for retrieving the adaptation data
(e.g., an accent-based pronunciation modification algorithm) to the
target device (e.g., a speech-controlled television), wherein the
adaptation data is configured to be applied to the target device
(e.g., the algorithm is designed to be run at least once as part of
the speech processing done by the target device) to assist in
execution of the speech-facilitated transaction (e.g., changing the
channel on the speech-controlled television).
[0138] Referring again to FIG. 9A, operation 704 may include
operation 906 depicting transmitting a location at which the
adaptation data is configured to be transmitted, said location
transmitted to the target device, wherein the adaptation data is
configured to be applied to the target device to assist in
execution of the speech-facilitated transaction. For example, FIG.
3, e.g., FIG. 3A, shows adaptation data retrieval location
transmission to target device facilitating module 306 transmitting
a location (e.g., an intranet address) at which the adaptation data
(e.g., a sentence diagramming path selection algorithm) is
configured to be transmitted (e.g., the location stores adaptation
data that is ready for transmission to various target devices,
e.g., a specific location on a company network) to the target
device (e.g., a company computer that is part of a business
enterprise solution), wherein the adaptation data is configured to
be applied to the target device (e.g., the sentence diagramming
path selection algorithm is used by the company computer to
determine the best sentence diagramming paths for use with the user
that is currently logged on to the company computer) to assist in
execution of the speech-facilitated transaction (e.g., typing a
memo into a word processor).
[0139] Referring again to FIG. 9A, operation 704 may include
operation 840 depicting facilitating transmission of the adaptation
data to a target device, wherein the adaptation data represents a
pronunciation of one or more words in a particular language spoken
by the particular party. For example, FIG. 3, e.g., FIG. 3A, shows
adaptation data representing pronunciation of one or more words in
a particular language spoken by the particular party transmission
to target device facilitating module 308 facilitating transmission
(e.g., taking one or more steps that assist in the transmission of)
of the adaptation data (e.g., an uncommon word pronunciation guide)
to a target device (e.g., an airline ticket dispensing machine),
wherein the adaptation data represents a pronunciation of one or
more words in a particular language (e.g., Spanish) spoken by the
particular party (e.g., the user, who, since they are in an
airport, may not be a native speaker of the language).
[0140] Referring again to FIG. 9A, operation 908 may include
operation 910 depicting facilitating transmission of the adaptation
data to a target device, wherein the adaptation data represents a
pronunciation of one or more words in a particular language spoken
by the particular party that is different from a language for which
the target device is designed to operate. For example, FIG. 3,
e.g., FIG. 3A, shows adaptation data representing pronunciation of
one or more words in a particular language spoken by the particular
party that is different from a target-device operation configured
language transmission to target device facilitating module 310
facilitating transmission of the adaptation data (e.g., a
pronunciation guide keyed to a language seen as "foreign" from the
target device perspective) to a target device (e.g., an airline
ticket dispensing machine), wherein the adaptation data represents
a pronunciation of one or more words in a particular language
(e.g., French) spoken by the particular party that is different
from a language for which the target device is designed to operate
(e.g., English).
[0141] Referring now to FIG. 9B, operation 704 may include
operation 912 depicting selecting particular adaptation data from
the adaptation data. For example, FIG. 3, e.g., FIG. 3B, shows
particular adaptation data selecting from adaptation data module
312 selecting particular adaptation data (e.g., a set of proper
noun pronunciations, e.g., city names) from the adaptation data
(e.g., word pronunciations).
[0142] Referring again to FIG. 9B, operation 704 may include
operation 914 depicting facilitating transmission of the particular
adaptation data to the target device. For example, FIG. 3, e.g.,
FIG. 3B, shows particular adaptation data to target device
transmission facilitating module 314 facilitating transmission
(e.g., specifying a protocol for transmission) of the particular
adaptation data (e.g., the set of proper noun pronunciations) to
the target device (e.g., the automated drive-thru order taking
machine).
[0143] Referring again to FIG. 9B, operation 912 may include
operation 916 depicting accessing adaptation data from a remote
location. For example, FIG. 3, e.g., FIG. 3B, shows adaptation data
from remote location accessing module 316 accessing (e.g. reading)
adaptation data (e.g., a proper noun pronunciation database) from a
remote location (e.g., a remote sever).
[0144] Referring again to FIG. 9B, operation 912 may include
operation 918 depicting selecting particular adaptation data from
the accessed adaptation data. For example, FIG. 3, e.g., FIG. 3B,
shows particular adaptation data selecting from accessed adaptation
data module 318 selecting particular adaptation data (e.g., a
particular set of proper noun pronunciations, e.g., names of
neighborhoods in a city in which the particular party is located)
from the accessed adaptation data (e.g., the accessed adaptation
data is a list of more proper noun pronunciations).
[0145] Referring again to FIG. 9B, operation 912 may include
operation 920 depicting retrieving the particular adaptation data
from the accessed adaptation data. For example, FIG. 3, e.g., FIG.
3B, shows particular adaptation data from accessed adaptation data
retrieving module 320 retrieving the particular adaptation data
(e.g., the names of neighborhoods of the city, e.g., for
Washington, D.C., retrieving the names "Alexandria," "Adams
Morgan," "Foggy Bottom," "Chinatown," and "DuPont Circle") from the
accessed adaptation data (e.g., a list of more proper noun
pronunciations, not all of which may be retrieved).
[0146] Referring again to FIG. 9B, operation 912 may include
operation 922 depicting selecting particular adaptation data based
on at least one property of the target device. For example, FIG. 3,
e.g., FIG. 3B, shows particular adaptation data selecting based on
at least one target device property module 322 selecting particular
adaptation data (e.g., a list of the way that the particular party
pronounces ten words, e.g., the numbers zero through nine) based on
at least one property of the target device (e.g., the target device
is an automated teller machine that processes a lot of speech
containing numbers).
[0147] Referring again to FIG. 9B, operation 922 may include
operation 924 depicting selecting a subset of adaptation data as
the particular adaptation data based on at least one property of
the target device. For example, FIG. 3, e.g., FIG. 3B, shows subset
of adaptation data selecting based on at least one target device
property module 324 selecting a subset of adaptation data (e.g., a
phrase completion algorithm tailored to ordering food) as the
particular adaptation data (e.g., the phrase completion algorithm
tailored to ordering food) based on at least one property of the
target device (e.g., that the target device is an automated
drive-thru system)
[0148] Referring again to FIG. 9B, operation 924 may include
operation 926 depicting selecting a portion of an inflection
database as the particular adaptation data based on at least one
property of the target device. For example, FIG. 3, e.g., FIG. 3B,
shows portion of inflection database selecting based on at least
one target device property module 326 selecting a portion of an
inflection database (e.g., selecting the inflections dealing with
words likely to be used in the speech-facilitated transaction) as
the particular adaptation data (e.g., the adaptation data has an
inflection database with many words, and the particular adaptation
data selects some of those words) based on at least one property of
the target device (e.g., the target device is a video game system
playing a warfare game, e.g., "Call of Duty," so words are selected
from the inflection database that are related to commands given in
a war game, e.g., "take cover," "concentrate fire on the eastern
ridge," etc.).
[0149] Referring again to FIG. 9B, operation 926 may include
operation 928 depicting selecting a portion of an inflection
database as the particular adaptation data based on one or more
words associated with the target device. For example, FIG. 3, e.g.,
FIG. 3B, shows portion of inflection database selecting based on
one or more words associated with target device module 328
selecting a portion of an inflection database (e.g., one or more
words from a larger inflection database containing more words than
are selected) as the particular adaptation data (e.g., words from
the inflection database including "defrost," "power level," and the
numbers "one" to "sixty," based on one or more words associated
with the target device (e.g., a speech-commanded microwave, which
is commanded by words like "defrost," and "power level," and uses
the numbers one to sixty to understand time (e.g., forty-five
seconds")).
[0150] Referring again to FIG. 9B, operation 928 may include
operation 930 depicting selecting a portion of an inflection
database as the particular adaptation data based on one or more
words associated with an automated teller machine device. For
example, FIG. 3, e.g., FIG. 3B shows portion of inflection database
selecting based on one or more words associated with an automated
teller device module 330 selecting a portion of an inflection
database (e.g., a portion of the inflection database that includes
words such as "deposit," "withdraw," "checking account," and
numbers) as the particular adaptation data (e.g., an inflection
database of one or more words) based on one or more words
associated with an automated teller machine (e.g., words such as
"deposit," "withdraw," "checking account," and numbers).
[0151] Referring again to FIG. 9B, operation 930 may include
operation 932 depicting selecting a portion of an inflection
database that includes words related to money as the particular
adaptation data, wherein words related to money are selected on a
basis of a determination that the words related to money are words
commonly used to operate the automated teller machine device. For
example, FIG. 3, e.g., FIG. 3B, shows portion of inflection
database selecting based on words related to money determined to be
associated with an automated teller device module 332 selecting a
portion of an inflection database that includes words related to
money (e.g., "cash," "checking," "deposit," "withdraw") as the
particular adaptation data, wherein words related to money are
selected on a basis of a determination that the words related to
money are words commonly used to operate the automated teller
machine device (e.g., this determination may happen at the time of
transaction, or may happen when the machine is first installed, or
may happen at periodic or nonperiodic intervals).
[0152] Referring now to FIG. 9C, operation 922 may include
operation 934 depicting receiving information regarding the
property of the target device from the target device. For example,
FIG. 3, e.g., FIG. 3C, shows information regarding the at least one
property of the target device receiving from target device module
334 receiving information regarding the property of the target
device (e.g., receiving information identifying the target device
as an audio/visual receiver) from the target device (e.g., the
audio/visual receiver).
[0153] Referring again to FIG. 9C, operation 922 may include
operation 936 depicting selecting the particular adaptation data
based on at least the received property of the target device. For
example, FIG. 3, e.g., FIG. 3C, shows particular adaptation data
selecting based on at least the received property of the target
device module 336 selecting the particular adaptation data (e.g.,
selecting a portion of a pronunciation dictionary that deals with
words related to the menu for the drive thru-terminal at which the
user is ordering) based on at least the received property (e.g.,
that the drive-thru terminal is a McDonald's drive thru terminal,
and uses words like "Big Mac" and "quarter-pounder") of the target
device (e.g., an automated McDonald's drive thru menu).
[0154] Referring again to FIG. 9C, operation 934 may include
operation 938 depicting receiving a list of at least one word that
the target device commonly receives as a command, from the target
device. For example, FIG. 3, e.g., FIG. 3C, shows information
regarding at least one word commonly used as a target device
command receiving from target device module 338 receiving a list of
at least one word (e.g., "lock door," "activate alarm," "call
police") that the target device (a voice controlled home security
system) commonly receives as a command, from the target device
(e.g., the home security system transmits at least one word that is
used to command it, the command word may be a word that the device
has been programmed to accept, either by the user or by the
manufacturer, or it may be based on common words that home security
systems receive").
[0155] Referring again to FIG. 9C, operation 938 may include
operation 940 depicting receiving a list of at least one word that
a digital video disc player commonly receives as a command, from
the digital video disc player. For example, FIG. 3, e.g., FIG. 3C,
shows information regarding at least one word commonly used to
command a digital video disc player command receiving from the
digital video disc player module 340 receiving a list of at least
one word (e.g., "play," "stop," and "fast-forward") that a digital
video disc player (e.g., a Samsung Blu-ray player) commonly
receives as a command, from the digital video disc player (e.g.,
the Samsung Blu-ray player).
[0156] Referring again to FIG. 9C, operation 940 may include
operation 942 depicting receiving a list of at least one word that
a digital video disc player commonly receives as a command, the
list of at least one word including the word "play," the list
received from the digital video disc player. For example, FIG. 3,
e.g., FIG. 3C, shows command play as a word commonly used to
command a digital video disc player receiving from the digital
video disc player module 342 receiving a list of at least one word
that a digital video disc player (e.g., a Sony DVD player) commonly
receives as a command, the list of at least one word including the
word play (e.g., "play" being a word commonly used by the Sony DVD
player to play a disc that has been inserted into the device), the
list received from the digital video disc player (e.g., the Sony
DVD player).
[0157] Referring again to FIG. 9C, operation 922 may include
operation 944 depicting selecting a subset of adaptation data as
the particular adaptation data based on a mode of the target
device. For example, FIG. 3, e.g., FIG. 3C, shows particular
adaptation data selecting based on a target device mode module 344
selecting a subset of adaptation data (e.g., pronunciation data for
the word "broil") as the particular adaptation data based on a mode
(e.g., a kitchen device that can operate as a convection oven or as
a microwave, and in an example, is operating as a convection oven,
thus using words such as "broil" in convection oven mode) of the
target device (e.g., the device that can operate as a convection
oven or as a microwave).
[0158] Referring now to FIG. 9D, operation 922 may include
operation 946 depicting selecting a subset of adaptation data as
the particular adaptation data based on a type of the target
device. For example, FIG. 3, e.g., FIG. 3D, shows particular
adaptation data selecting based on a type of target device module
346 selecting a subset of adaptation data (e.g., pronunciations of
words related to the type of the device) as the particular
adaptation data based on a type (e.g., is a piece of audio visual
equipment, or is a piece of kitchen equipment, or home security
equipment) of the target device (a piece of audio visual equipment,
e.g., a voice-controlled Panasonic television).
[0159] Referring again to FIG. 9D, operation 946 may include
operation 948 depicting selecting a subset of adaptation data that
was derived at least in part from one or more devices of a same
type as the target device as the particular adaptation data, based
on a type of the target device. For example, FIG. 3, e.g., FIG. 3D,
shows subset of adaptation data derived at least in part from one
or more devices of a same type as the target device selecting
module 348 selecting a subset of adaptation data (e.g., selecting a
phrase completion algorithm from one or more phrase completion
algorithms) that was derived at least in part from one or more
devices (e.g., the phrase completion algorithm is selected by
selecting a phrase completion algorithm having the best success
rate when previously used with the type of device, e.g., navigation
system) of a same type (e.g., navigation systems, whether or not
from the same brand) as the target device (e.g., a Garmin Nuvi
navigation device) as the particular adaptation data (e.g., the
selected phrase completion algorithm), based on a type of the
target device (e.g., the Garmin Nuvi is a navigation device).
[0160] Referring again to FIG. 9D, operation 948 may include
operation 950 depicting selecting a subset of adaptation data that
was derived at least in part from one or more speech interactions
by the particular party with one or more devices of the same type
as the target device as the particular adaptation data, based on a
type of the target device. For example, FIG. 3, e.g., FIG. 3D,
shows subset of adaptation data derived at least in part from one
or more speech interactions with one or more devices of a same type
as the target device selecting module 350 selecting a subset of
adaptation data (e.g., pronunciations of common video game terms,
e.g., "jump," "shoot," "duck," and "fire") that was derived at
least in part from one or more speech interactions by the
particular party (e.g., the particular party playing other
speech-controlled games) with one or more devices of the same type
(e.g., video game systems, which may or may not be the same type of
system (e.g., Xbox, computer games, Sony PlayStation), and may or
may not be the same type of game (e.g., war game, shooting game,
sports game) as the target device (e.g., a voice-controlled video
game system) as the particular adaptation data (e.g.,
pronunciations of video game words), based on a type (e.g., video
game system) of the target device (e.g., voice controlled video
game system from Microsoft).
[0161] Referring again to FIG. 9D, operation 950 may include
operation 952 depicting selecting a subset of adaptation data that
was derived at least in part from one or more speech interactions
by the particular party with one or more home entertainment
devices, as the particular adaptation data, based on the target
device being a television that accepts voice input. For example,
FIG. 3, e.g., FIG. 3D, shows subset of adaptation data derived at
least in part from one or more speech interactions with home
entertainment devices when the target device is a voice input
accepting television selecting module 352 selecting a subset of
adaptation data (e.g., pronunciations of movies, e.g., "Spider-Man"
and "The Social Network" that was derived at least in part from
speech interactions by the particular party (e.g., the user
ordering different movies) with one or more home entertainment
devices (e.g., a speech-enabled streaming video delivery device),
as the particular adaptation data, based on the target device being
a television (e.g., a device of a same type, e.g., "audio visual
device" or "home entertainment device") that accepts voice input
(e.g., a voice-controlled Sony television with an Internet
connection for a streaming video service like Netflix).
[0162] Referring again to FIG. 9D, operation 950 may include
operation 954 depicting selecting a subset of adaptation data that
was derived at least in part from one or more speech interactions
by the particular party with one or more televisions that accept
voice input, based on the target device being a television that
accepts voice input. For example, FIG. 3, e.g., FIG. 3D, shows
subset of adaptation data derived at least in part from one or more
speech interactions with one or more televisions when the target
device is a voice input accepting television selecting module 354
selecting a subset of adaptation data (e.g., a phrase completion
algorithm useful for voice-controlled televisions selected from one
or more phrase completion algorithms available as adaptation data)
that was derived in part from one or more speech interactions by
the particular party (e.g., the watcher of the television) with one
or more televisions that accept voice input, based on the target
device being a television that accepts voice input.
[0163] Referring now to FIG. 9E, operation 922 may include
operation 956 depicting selecting a subset of adaptation data as
the particular adaptation data based on a speech receiving
component of the target device. For example, FIG. 3, e.g., FIG. 3E,
shows particular adaptation data selecting based on a speech
receiving component of target device module 356 selecting a subset
of adaptation data (e.g., selecting a minimal-processing language
processing algorithm from a list of available algorithms) as the
particular adaptation data based on a speech receiving component
(e.g., a particular speech receiving component that has low
processing power and needs to be able to process the speech
quickly) of the target device (e.g., an automated train ticket
dispensing terminal disposed in New York City's Penn Station, e.g.,
which terminal has low processing power but needs to process lots
of speech quickly).
[0164] Referring again to FIG. 9E, operation 356 may include
operation 958 depicting selecting a subset of adaptation data as
the particular adaptation data based on a quality of microphone of
the target device. For example, FIG. 3, e.g., FIG. 3E, shows
particular adaptation data selecting based on a quality of a
microphone of target device module 358 selecting a subset of
adaptation data (e.g., a match-closeness algorithm that requires
high quality voice samples from a list of one or more algorithms)
as the particular adaptation data based on a quality of microphone
(e.g., a high-quality microphone attached to a company computer
used to dictate memorandums) of the target device (e.g., a high
quality microphone used on a company computer in an enterprise
environment to command the computer using speech).
[0165] Referring again to FIG. 9E, operation 356 may include
operation 960 depicting selecting a subset of adaptation data as
the particular adaptation data based on a type of microphone of the
target device. For example, FIG. 3, e.g., FIG. 3E, shows particular
adaptation data selecting based on a type of a microphone of target
device module 360 selecting a subset of adaptation data (e.g.,
selecting an echo-reducing pronunciation algorithm) as the
particular adaptation data based on a type of microphone (e.g.,
unidirectional, omni-directional, etc.) of the target device (e.g.,
a speech-enabled automated teller machine device).
[0166] Referring again to FIG. 9E, operation 922 may include
operation 962 depicting selecting a subset of adaptation data as
the particular adaptation data based on at least one property of a
motor vehicle. For example, FIG. 3, e.g., FIG. 3E, shows particular
adaptation data selecting based on at least one motor vehicle
property module 362 selecting a subset of adaptation data (e.g.,
selecting pronunciations of particular vocabulary words that a
particular motor vehicle is designed to use, e.g., "move left
mirror," in a vehicle whose mirror systems are speech-enabled,
would be selected in this example, but perhaps not selected in a
motor vehicle whose mirror systems are not speech enabled) as the
particular adaptation data based on at least one property (e.g.,
speech-enabled mirror control systems) of a motor vehicle.
[0167] Referring again to FIG. 9E, operation 962 may include
operation 964 depicting selecting a subset of adaptation data as
the particular adaptation data based on a velocity of the motor
vehicle. For example, FIG. 3, e.g., FIG. 3E, shows particular
adaptation data selecting based on motor vehicle velocity module
364 selecting a subset of adaptation data (e.g., a high-ambient
noise level filtration algorithm, from one or more available
algorithms, each designed to operate most efficiently at various
amounts of ambient noise) as particular adaptation data based on a
velocity (e.g., the higher the velocity, the more likely there is
high ambient noise from engine, wind, road vibrations, and the
like) of the motor vehicle
[0168] Referring again to FIG. 9E, operation 962 may include
operation 966 depicting selecting a subset of adaptation data as
the particular adaptation data based on a vibration level of the
motor vehicle. For example, FIG. 3, e.g., FIG. 3E, shows particular
adaptation data selecting based on motor vehicle vibration level
module 366 selecting a subset of adaptation data (e.g., a low
ambient noise level dependent filtration algorithm, from one or
more algorithms for processing received speech data) as the
particular adaptation data based on a vibration level (e.g., the
ambient noise is assumed to go up as measured vibration levels of
the vehicle go up) of the motor vehicle.
[0169] Referring now to FIG. 9F, operation 912 may include
operation 968 depicting selecting particular adaptation data from
the adaptation data based on a condition of an environment in which
the speech-facilitated transaction is configured to be carried out.
For example, FIG. 3, e.g., FIG. 3F, shows particular adaptation
data selecting based on an environment condition of an environment
of the speech-facilitated transaction module 368 selecting
particular adaptation data (e.g., an algorithm for use in speech
processing in high noise environments) from the adaptation data
(e.g., a list of one or more algorithms configured to be used in
different scenarios) based on a condition of an environment (e.g.,
a noisy environment, e.g., an automated teller machine at a
baseball stadium) in which the speech-facilitated transaction
(e.g., withdrawing money) is configured to be carried out.
[0170] Referring again to FIG. 9F, operation 968 may include
operation 970 depicting selecting particular adaptation data from
the adaptation data based on an ambient noise level in the
environment in which the speech-facilitated transaction is
configured to be carried out. For example, FIG. 3, e.g., FIG. 3F,
shows particular adaptation data selecting based on an ambient
noise level of an environment of the speech-facilitated transaction
module 370 selecting particular adaptation data (e.g., selecting a
best-guess algorithm that requires less accuracy for
interpretation, from one or more algorithms) from the adaptation
data (e.g., one or more algorithms) based on an ambient noise level
in the environment (e.g., a loud subway station where the
speech-enabled ticket terminal is located) in which the
speech-facilitated transaction (e.g., buying a subway ticket) is
configured to be carried out.
[0171] Referring again to FIG. 9F, operation 968 may include
operation 972 depicting selecting particular adaptation data from
the adaptation data based on a distance between the particular
party and the target device. For example, FIG. 3, e.g., FIG. 3F,
shows particular adaptation data selecting based on a distance
between the particular party and the target device during the
speech-facilitated transaction module 372 selecting particular
adaptation data (e.g., a signal boosting algorithm, and a
particular sentence diagramming path selection algorithm) from the
adaptation data (e.g., many algorithms for processing speech, of
which multiple algorithms may be selected and used) based on a
distance (e.g., greater than l1, to the point where signal boosting
could be useful) between the particular party and the target device
(e.g., a drive-thru ordering menu where the user is in a giant
truck and is far from the microphone).
[0172] Referring again to FIG. 9F, operation 968 may include
operation 974 depicting selecting particular adaptation data from
the adaptation data based on an amount of interference present in
an environment in which the speech-facilitated transaction is
configured to be carried out. For example, FIG. 3, e.g., FIG. 3F,
shows particular adaptation data selecting based on an amount of
interference present in an environment of the speech-facilitated
transaction module 374 selecting particular adaptation data (e.g.,
a particular pronunciation adjustment algorithm) from the
adaptation data (e.g., from a list of available speech processing
algorithms, from which one or more may be applied or presented for
application) based on an amount of interference (e.g., noise,
static on a line, etc.) present in an environment (e.g., the
surroundings, e.g., 7th and F street next to Verizon Center) in
which the speech-facilitated transaction (e.g., the use of an
automated teller machine) is configured to be carried out).
[0173] Referring again to FIG. 3F, operation 912 may include
operation 976 depicting receiving a selection of particular
adaptation data from the particular party. For example, FIG. 3,
e.g., FIG. 3F, shows selection of particular adaptation data from
particular party receiving module 376 receiving a selection of
particular adaptation data (e.g., the user selects a set of one or
more pronunciations of vocabulary words, based on what types of
words that user is intending to use, e.g., a video game system
might load a video game, and then the user might be prompted to
select a set of vocabulary words, e.g., "words for a football
game," or "words from a World War II shooting game) from the
particular party (e.g., the game player).
[0174] Referring again to FIG. 3F, operation 976 may include
operation 978 depicting presenting adaptation data to the
particular party for selection from the presented adaptation data.
For example, FIG. 3, e.g., FIG. 3F, shows adaptation data
presenting to particular party for selection of particular
adaptation data module 378 presenting adaptation data (e.g.,
displaying various sets of adaptation data for the user to select
on a screen, or reading out lout selectable sets of adaptation data
through a speaker or headphone) to the particular party for
selection (e.g., the user makes a selection of one or more sets of
adaptation data from the one or more sets presented) from the
presented adaptation data (e.g., one or more sets of pronunciations
of words, or one or more algorithms).
[0175] Referring again to FIG. 3F, operation 976 may include
operation 980 depicting receiving a selection of adaptation data
from the particular party as particular adaptation data. For
example, FIG. 3, e.g., FIG. 3F, shows selection of particular
adaptation data from the particular party receiving module 380
receiving a selection of adaptation data (e.g., the user selects a
set of adaptation data from the presented adaptation data by
pushing a button on a touchscreen) as particular adaptation
data.
[0176] Referring now to FIG. 9G, operation 912 may include
operation 982 depicting selecting particular adaptation data from
the adaptation data at least partly based on previously acquired
user preferences. For example, FIG. 3, e.g., FIG. 3G, shows
selection of particular adaptation data based on previously
acquired user preferences module 382 selecting particular
adaptation data (e.g., selecting a set of vocabulary words) from
the adaptation data at least partly based on previously acquired
user preferences (e.g., if a user previously has set an option for
"fast food menus," or if a user merely likes cheeseburgers and
orders a lot of them, then these are previously acquired user
preferences that can be used to select adaptation data (e.g.,
pronunciation sets that include fast-food or cheeseburger-related
words, e.g., "mayonnaise," and "sesame seed buns").
[0177] Referring again to FIG. 9G, operation 912 may include
operation 984 depicting transmitting one or more options for
selecting adaptation data to the target device. For example, FIG.
3, e.g., FIG. 3G, shows transmitting options for selecting
adaptation data to target device module 384 transmitting one or
more options for selecting adaptation data (e.g., transmitting a
"noise level dependent filtration algorithm," option a "basic
pronunciation adjustment algorithm" option, and an "utterance
ignoring algorithm" option, of which one or more of these options
may be selected by the target device based on its processing, e.g.,
which modules it determines will be the most useful, or by random
or other selection) to the target device (e.g., an onboard vehicle
command system).
[0178] Referring again to FIG. 9G, operation 912 may include
operation 986 depicting receiving a selection of adaptation data
from the target device. For example, FIG. 3, e.g., FIG. 3G, shows
target device selection of adaptation data receiving module 386
receiving a selection of adaptation data (e.g., the target device
selected the "utterance ignoring algorithm") from the target device
(e.g., the onboard vehicle command system).
[0179] Referring again to FIG. 9G, operation 912 may include
operation 988 depicting selecting particular adaptation data from
the adaptation data based on the selection of adaptation data
selected by the target device. For example, FIG. 3, e.g., FIG. 3G,
shows particular adaptation data selection based on received
adaptation data selected by target device module 388 selecting
particular adaptation data (e.g., selecting the "utterance ignoring
algorithm) from the adaptation data (e.g., which may include the
algorithms presented for selection, and also, in some embodiments,
additional algorithms or other data) based on the selection of
adaptation data selected by the target device (e.g., the onboard
vehicle command system).
[0180] Referring again to FIG. 9G, operation 902 may include
operation 990 depicting facilitating transmission of the adaptation
data to a target device when there is an indication from the target
device of initiation of a speech-facilitated transaction between
the target device and the particular party, wherein the adaptation
data is configured to be applied to the target device to assist in
execution of the speech-facilitated transaction. For example, FIG.
3, e.g., FIG. 3G, shows particular party-correlated adaptation data
receiving facilitated by particular party associated particular
device upon indication from target device of initiation of
speech-facilitated transaction between target device and particular
party module 390 facilitating transmission of the adaptation data
(e.g., a regional dialect application algorithm) to a target device
(e.g., a speech recognition-enabled ticket dispensing terminal)
when there is an indication from the target device (e.g., a user
presses the "start" button on the ticket dispensing terminal) of
initiation of a speech facilitated transaction (e.g., the
transaction of printing a previously-purchased ticket has been
initiated) between the target device (e.g., the ticket dispensing
terminal) and the particular party (e.g., the user), wherein the
adaptation data (e.g., the regional dialect application algorithm)
is configured to be applied to the target device (e.g., the target
device applies the regional dialect application algorithm to the
received speech in order to assist in processing the received
speech) to assist in execution of the speech-facilitated
transaction (e.g., printing out a previously-purchased ticket).
[0181] FIGS. 10A-10G depict various implementations of operation
706, according to embodiments. Referring to FIG. 10A, operation 706
may include operation 1002 depicting assisting reception of
adaptation result data at a location, said adaptation result data
based on at least one aspect of the speech-facilitated transaction
between the particular party and the target device. For example,
FIG. 4, e.g., FIG. 4A, shows adaptation result data based on a
result of at least one aspect of a speech-facilitated transaction
reception at a location assisting module 402 assisting reception
(e.g., performing at least one operation or task related to
receiving) of adaptation result data (e.g., an indication, e.g., a
numeric representation, of the success of the speech-facilitated
transaction) at a location (e.g., a server that collects the
adaptation result data), said adaptation result data based on at
least one aspect (e.g., a success of) the speech-facilitated
transaction between the particular party (e.g., the user) and the
target device (e.g., the company computer with speech-enabled
commands).
[0182] Referring again to FIG. 10A, operation 706 may include
operation 1004 depicting receiving adaptation result data that is
based on at least one aspect of the speech-facilitated transaction
between the particular party and the target device. For example,
FIG. 4, e.g., FIG. 4A, shows adaptation result data based on a
result of at least one aspect of a speech-facilitated transaction
receiving module 404 receiving adaptation result data (e.g., a list
of one or more questions asked by the automated teller machine
device and the user's response to the one or more questions) that
is based on at least one aspect (e.g., the user's responses) of the
speech-facilitated transaction between the particular party (e.g.,
the user) and the target device (e.g., the automated teller machine
device).
[0183] Referring again to FIG. 10A, operation 706 may include
operation 1006 depicting providing an address of a location
configured to receive adaptation result data that is based on at
least one aspect of a speech-facilitated transaction between the
particular party and the target device. For example, FIG. 4, e.g.,
FIG. 4A, shows address of location configured to receive adaptation
result data based on a result of at least one aspect of a
speech-facilitated transaction providing module 406 providing an
address (e.g., a secure web address) of a location configured to
receive (e.g., is capable of receiving data) adaptation result data
(e.g., a user's survey ranking of the usefulness of the speech
portion of the speech-facilitated transaction) between the
particular party (e.g., the user) and the target device (e.g., the
home computer on a home network).
[0184] Referring again to FIG. 10A, operation 706 may include
operation 1008 depicting receiving an address of a location at
which adaptation result data is configured to be received, said
adaptation result data based on at least one aspect of a
speech-facilitated transaction between the particular party and the
target device. For example, FIG. 4, e.g., FIG. 4A, shows address of
location configured to receive adaptation result data based on a
result of at least one aspect of a speech-facilitated transaction
receiving module 408 receiving an address of a location (e.g., a
networked computer sends a location that is capable of receiving
the adaptation result data) at which adaptation result data (e.g.,
an automatically-generated representation of a user's perceived
state of mind at the end of the speech-facilitated transaction) is
configured to be received, said adaptation result data based on at
least one aspect of a speech-facilitated transaction (e.g.,
interacting with an automated telephony system) between the
particular party (e.g., the user) and the target device (e.g., a
networked IP phone, e.g., a Cisco IP phone 7945).
[0185] Referring now to FIG. 10B, operation 706 may include
operation 1010 depicting facilitating reception of adaptation
result data that is based on a result of the speech-facilitated
transaction between the particular party and the target device. For
example, FIG. 4, e.g., FIG. 4B, shows adaptation result data based
on a result of the speech-facilitated transaction reception
facilitating module 410 facilitating reception of adaptation result
data (e.g., a user-provided feedback) that is based on a result of
the speech facilitated transaction between the particular party
(e.g., the user) and the target device (e.g., an automated ticket
dispensing machine).
[0186] Referring again to FIG. 10B, operation 1010 may include
operation 1012 depicting facilitating reception of adaptation
result data that is based on a measure of success of at least one
portion of the speech-facilitated transaction between the
particular party and the target device. For example, FIG. 4, e.g.,
FIG. 4B, shows adaptation result data based on a measure of success
of the speech-facilitated transaction reception facilitating module
412 facilitating reception (e.g., providing at least one step for,
e.g., generating a signal that a survey should be sent out
requesting feedback) of adaptation result data (e.g., a user's
written response to a survey question regarding her experience in
conducting a speech-facilitated transaction, filled out at a later
time) that is based on a measure of success (e.g., the user's
perception of the success of the transaction) of at least one
portion of the speech-facilitated transaction (e.g., using an
in-vehicle automated emergency response system (e.g., to contact
police, unlock doors, etc.) between the particular party (e.g., the
user) and the target device (e.g., an in-vehicle automated
emergency response voice-responding system)
[0187] Referring again to FIG. 10B, operation 1012 may include
operation 1014 depicting facilitating reception of adaptation
result data that comprises a representation of success of at least
one portion of the speech-facilitated transaction between the
particular party and the target device. For example, FIG. 4, e.g.,
FIG. 4B, shows adaptation result data based on a numeric
representation of success of the speech-facilitated transaction
reception facilitating module 414 facilitating reception (e.g.,
storing the address of the server that will receive the adaptation
data) of adaptation result data (e.g., a letter grade assigned to
the transaction by a piece of software running on a network that
evaluates, separately from the processing of the speech, a success
of the speech portion of the transaction, e.g., composing an email)
that comprises a representation of success (e.g. a letter grade) of
at least one portion (e.g., the speech portion) of the
speech-facilitated transaction (e.g., composing an email using a
voice system with the headset as the particular device) between the
particular party (e.g., the user) and the target device (e.g., the
computer configured to receive speech data).
[0188] Referring again to FIG. 10B, operation 1014 may include
operation 1016 depicting facilitating reception of adaptation
result data that comprises a representation of success of at least
one portion of the speech-facilitated transaction between the
particular party and the target device, said representation of
success provided by the particular party. For example, FIG. 4,
e.g., FIG. 4B, shows adaptation result data comprising a particular
party provided representation of success of the speech-facilitated
transaction reception facilitating module 416 facilitating
reception (e.g., receiving) of adaptation result data (e.g., a
response to a survey question of "How would you rate this
transaction from "very efficient" to "very inefficient") that
comprises a representation of success of at least one portion of
the speech-facilitated transaction (e.g., printing an airline
ticket) between the particular party (e.g., the user) and the
target device (e.g., an automated airline ticket dispenser), said
representation of success (e.g., the survey answer) provided by the
particular party (e.g., the user verbally responds to the survey
question)
[0189] Referring again to FIG. 10B, operation 1014 may include
operation 1018 depicting facilitating reception of adaptation
result data that comprises a representation of success of at least
one portion of the speech-facilitated transaction between the
particular party and the target device, said representation of
success provided by the target device. For example, FIG. 4, e.g.,
FIG. 4B, shows adaptation result data comprising a target device
provided representation of success of the speech-facilitated
transaction reception facilitating module 418 facilitating
reception of adaptation result data (e.g., a numeric representation
of the target device's analysis of the transaction, based on
objective factors, e.g., how many times the same question had to be
repeated, etc.) that comprises a representation of success (e.g.,
the numeric representation calculated by the target device) of at
least one portion of the speech-facilitated transaction (e.g.,
ordering a hamburger and fries from an automated drive-thru window)
between the particular party (e.g., the user) and the target device
(e.g., the automated drive-thru window), said representation of
success provided by the target device (e.g., the target device
collects the objective factors and generates a numeric
representation of success of the speech-facilitated
transaction).
[0190] Referring again to FIG. 10B, operation 1014 may include
operation 1020 depicting facilitating reception of a non-numeric
representation of success of the speech-facilitated transaction
between the particular party and the target device. For example,
FIG. 4, e.g., FIG. 4B, shows Adaptation result data comprising a
non-numeric representation of success of the speech-facilitated
transaction reception facilitating module 420 facilitating
reception of a non-numeric representation of success (e.g., an
open-ended survey question response) of the speech-facilitated
transaction (e.g., withdrawing money from a speech-enabled
automated teller machine device) between the particular party
(e.g., the user) and the target device (e.g., the automated teller
machine device).
[0191] Referring now to FIG. 10C, operation 1014 may include
operation 1022 depicting facilitating reception of adaptation
result data that comprises a numeric representation of success of
at least one portion of the speech-facilitated transaction between
the particular party and the target device. For example, FIG. 4,
e.g., FIG. 4C, shows adaptation result data comprising a numeric
representation of success of the speech-facilitated transaction
reception facilitating module 422 facilitating reception of
adaptation result data (e.g., a feedback score entered by the user,
e.g., 57 out of 100) that comprises a numeric representation of
success (e.g., 57/100) of at least one portion (e.g., the first
half of a financial transaction, e.g., accessing the checking
account) of the speech-facilitated transaction (e.g., transferring
money from a checking account to a savings account) between the
particular party (e.g., the user) and the target device (e.g., an
automated banking terminal).
[0192] Referring again to FIG. 10C, operation 1022 may include
operation 1024 depicting facilitating reception of a confidence
rate of correct interpretation of at least a portion of the
speech-facilitated transaction between the particular party and the
target device. For example, FIG. 4, e.g., FIG. 4C, shows adaptation
result data comprising a confidence rate of correct interpretation
of at least a portion of the speech-facilitated transaction
reception facilitating module 424 facilitating reception of a
confidence rate of correct interpretation (e.g., 75% likely that
the words "twenty dollars" of the speech transaction were correctly
interpreted) of at least a portion (e.g., the portion in which the
user says how much money she wants to withdraw) of the
speech-facilitated transaction (e.g., withdrawing twenty dollars
from a checking account) between the particular party (e.g., the
user) and the target device (e.g., the speech-enabled automated
teller machine device).
[0193] Referring again to FIG. 10C, operation 1022 may include
operation 1026 depicting facilitating reception of an
interpretation error rate of at least a portion of the
speech-facilitated transaction between the particular party and the
target device. For example, FIG. 4, e.g., FIG. 4C, shows adaptation
result data comprising an interpretation error rate of at least a
portion of the speech-facilitated transaction reception
facilitating module 426 facilitating reception of an interpretation
error rate (e.g., a rate at which it is determined that an
interpretation of the user's speech was incorrect) of at least a
portion of the speech-facilitated transaction (e.g., all the speech
commands given during one level of a game played by the user on a
speech-enabled game console) between the particular party (e.g.,
the user playing the game) and the target device (e.g., the video
game system).
[0194] Referring again to FIG. 10C, operation 706 may include
operation 1028 depicting facilitating reception of adaptation
result data comprising a list of at least one word that was
improperly interpreted during the speech-facilitated transaction.
For example, FIG. 4, e.g., FIG. 4C, shows adaptation result data
comprising a list of at least one word improperly interpreted
during speech-facilitated transaction reception facilitating module
428 facilitating reception of adaptation result data (e.g., a list
of phrases such as "Play Saving Private Ryan," "Eject DVD," and
"Fast-Forward 8.times.") comprising a list of at least one word
that was improperly interpreted (e.g., the phrases "Play Saving
Private Ryan," "Eject DVD," and "Fast-Forward 8.times." all were
improperly interpreted (e.g., interpreted into a command that was
not the user's desired command) during the speech-facilitated
transaction (e.g., during the user's attempt to watch a DVD on his
speech-enabled home theater system).
[0195] Referring now to FIG. 10D, operation 706 may include
operation 1030 depicting facilitating reception of adaptation
result data comprising a list of at least one word that was
improperly interpreted more than once during the speech-facilitated
transaction. For example, FIG. 4, e.g., FIG. 4D, shows adaptation
result data comprising a list of at least one word improperly
interpreted more than once during the speech-facilitated
transaction reception facilitating module 430 facilitating
reception (e.g., receiving) of adaptation result data (e.g., a list
of the pronunciation of the words "lock safe" by the user)
comprising a list of at least one word that was improperly
interpreted more than once (e.g., the user said "lock safe" three
times before it was recognized by the voice-enabled safe) during
the speech-facilitated transaction (e.g., locking the safe via
voice command).
[0196] Referring again to FIG. 10D, operation 706 may include
operation 1032 depicting facilitating reception of adaptation
result data comprising a table of at least one word that was
improperly interpreted during the speech-facilitated transaction,
and a number of times that the at least one word was improperly
interpreted during the speech-facilitated transaction. For example,
FIG. 4, e.g., FIG. 4D, shows adaptation result data comprising a
table of at least one word improperly interpreted and a number of
times the at least one word was improperly interpreted during the
speech-facilitated transaction reception facilitating module 432
facilitating reception of adaptation result data comprising a table
of at least one word that was improperly interpreted (e.g., "play")
during the speech-facilitated transaction (e.g., instructing a
speech-enabled media player to play a particular song), and a
number of times that the at least one word was improperly
interpreted (e.g., three) during the speech-facilitated transaction
(e.g., the user had to repeat the command four times (e.g., it was
properly interpreted on the fourth try)).
[0197] Referring again to FIG. 10D, operation 706 may include
operation 1034 depicting facilitating reception of adaptation
result data comprising a list of at least one question that was
asked by the target device at least twice consecutively. For
example, FIG. 4, e.g., FIG. 4D, shows adaptation result data
comprising a list of at least one question asked by the target
device at least twice consecutively reception facilitating module
434 facilitating reception of adaptation result data comprising a
list of at least one question (e.g., "what city are you traveling
to today") that was asked by the target device (e.g., an automated
airline ticket dispenser) at least twice consecutively (e.g.,
during the ticket-printing transaction, the automated airline
ticket dispenser repeated the question "what city are you traveling
to today" twice).
[0198] Referring again to FIG. 10D, operation 706 may include
operation 1036 depicting facilitating reception of adaptation
result data comprising a table of at least one question that was
asked by the target device at least twice consecutively, and one or
more answers given to the at least one question by the particular
party. For example, FIG. 4, e.g., FIG. 4D, shows adaptation result
data comprising a list of at least one question asked by the target
device at least twice consecutively and one or more answers given
to the at least one question reception facilitating module 436
facilitating reception of adaptation result data comprising a table
of at least one question (e.g., "please state your order") that was
asked by the target device (e.g., an automated drive-thru window,
and one or more answers given to the at least one question by the
particular party (e.g., "cheeseburger, French fries, and chocolate
shake").
[0199] Referring again to FIG. 10D, operation 706 may include
operation 1038 depicting facilitating reception of adaptation
result data comprising a table of at least one question that was
asked by the target device, and at least one corresponding answer
given by the particular party to the at least one question. For
example, FIG. 4, e.g., FIG. 4D, shows adaptation result data
comprising a table of at least one question asked by the target
device and at least one corresponding answer given by the
particular party reception facilitating module 438 facilitating
reception of adaptation result data comprising a table of at least
one question (e.g., "what number would you like to set the volume
to") that was asked by the target device (e.g., a speech-enabled
television), and at least one corresponding answer (e.g.,
"forty-five") given by the particular party (e.g., the user) to the
at least one question.
[0200] Referring now to FIG. 10E, operation 706 may include
operation 1040 depicting facilitating reception of adaptation
result data comprising at least one phoneme appearing in at least
one word that was improperly interpreted during the
speech-facilitated transaction. For example, FIG. 4, e.g., FIG. 4E,
shows adaptation result data comprising at least one phoneme
appearing in at least one word that was improperly interpreted
during the speech-facilitated transaction reception facilitating
module 440 facilitating reception of adaptation result data (e.g.,
one or more pronunciations of one or more phonemes) comprising at
least one phoneme (e.g., the "a" sound at the end of the word
"cafe") appearing in at least one word (e.g., "Hard Times Cafe")
that was improperly interpreted during the speech-facilitated
transaction (e.g., asking a portable navigation device for
directions to Hard Times Cafe).
[0201] Referring again to FIG. 10E, operation 1040 may include
operation 1042 depicting facilitating reception of adaptation
result data comprising at least one phoneme appearing in multiple
words that were improperly interpreted during the
speech-facilitated transaction. For example, FIG. 4, e.g., FIG. 4E,
shows adaptation result data comprising at least one phoneme that
was improperly interpreted during the speech-facilitated
transaction reception facilitating module 442 facilitating
reception of adaptation result data comprising at least one phoneme
(e.g., the "ay" sound in "play") appearing in multiple words (e.g.,
the word "play" was misinterpreted more than once) that were
improperly interpreted during the speech-facilitated transaction
(e.g., "play Saving Private Ryan").
[0202] Referring again to FIG. 10E, operation 1042 may include
operation 1044 depicting facilitating reception of adaptation
result data comprising at least one phoneme appearing in more than
one unique word that was improperly interpreted during the
speech-facilitated transaction, For example, FIG. 4, e.g., FIG. 4E,
shows adaptation result data comprising at least one phoneme
appearing in more than one unique word that was improperly
interpreted during the speech-facilitated transaction reception
facilitating module 444 facilitating reception of adaptation result
data comprising at least one phoneme (e.g., the "a" sound at the
end of the words "cafe" and "beret") appearing in more than one
unique word (e.g., "cafe" and "beret") that were improperly
interpreted (e.g., a sentence of "please give me directions to the
nearest cafe where berets are allowed to be worn inside," given to
a smart device that accepts speech and has navigational
capabilities) during the speech-facilitated transaction.
[0203] Referring again to FIG. 10E, operation 706 may include
operation 1046 depicting facilitating reception of adaptation
result data upon conclusion of the speech-facilitated transaction
between the particular party and the target device. For example,
FIG. 4, e.g., FIG. 4E, shows adaptation result data based on a
result of at least one aspect of a speech-facilitated transaction
reception facilitating upon conclusion of speech-facilitated
transaction module 446 facilitating reception (e.g., receiving
survey data) of adaptation result data (e.g., survey data filled
out by the user upon prompting from the target device) upon
conclusion (e.g., at the end) of the speech-facilitated transaction
(e.g., withdrawing money from a speech-enabled automated teller
machine device, and at the end, the device prompts for a survey)
between the particular party (e.g., the user) and the target device
(e.g., the speech-enabled automated teller machine device).
[0204] Referring again to FIG. 10E, operation 706 may include
operation 1048 depicting facilitating reception of adaptation
result data as a conclusion of the speech-facilitated transaction
between the particular party and the target device. For example,
FIG. 4, e.g., FIG. 4E, shows determining a conclusion of a speech
facilitated transaction based on facilitating reception of
adaptation result data module 448 facilitating reception (e.g.,
receiving) adaptation result data (e.g., a word frequency table
indicating how many times each word was spoken during the
transaction) as a conclusion (e.g., the reception of the word
frequency table indicates that the speech-facilitated transaction
is over) of the speech-facilitated transaction (e.g., dictating a
memorandum to a computer configured to receive speech input)
between the particular party (e.g., the user) and the target device
(e.g., the speech input-enabled computer used in an enterprise
setting).
[0205] Referring again to FIG. 10E, operation 706 may include
operation 1050 depicting facilitating reception of adaptation
result data during the speech-facilitated transaction between the
particular party and the target device. For example, FIG. 4, e.g.,
FIG. 4E, shows adaptation result data based on a result of at least
one aspect of a speech-facilitated transaction reception
facilitating during speech-facilitated transaction module 450
facilitating reception of adaptation result data (e.g., a
confidence rate that the previous phrase was correctly interpreted)
during the speech-facilitated transaction (e.g., while the user is
still giving commands to the audio/visual receiver) between the
particular party (e.g., the user) and the target device (e.g., the
speech-command enabled audio/visual receiver).
[0206] Referring again to FIG. 10E, operation 706 may include
operation 1052 depicting facilitating reception of adaptation
result data prior to completion of the speech-facilitated
transaction, For example, FIG. 4, e.g., FIG. 4E, shows adaptation
result data based on a result of at least one aspect of a
speech-facilitated transaction reception facilitating prior to
completing the speech-facilitated transaction module 452
facilitating reception of adaptation result data (e.g., a predicted
error rate of the words interpreted up to this point in the
speech-facilitated transaction) prior to completion of the
speech-facilitated transaction (e.g., before the player has
finished playing a level of a game, or finished giving all the
speech commands for a particular game level).
[0207] FIGS. 11A-11B depict various implementations of operation
708, according to embodiments. Referring to FIG. 11A, operation 708
may include operation 1102 depicting receiving instructions
regarding whether to modify the adaptation data at least partly
based on the adaptation result data. For example, FIG. 5, e.g.,
FIG. 5A, shows adaptation data modification instructions at least
partly based on adaptation result data receiving module 502
receiving instructions (e.g., "replace the pronunciation of the
word "cheese" in the pronunciation dictionary with the following
pronunciation") regarding whether to modify the adaptation data
(e.g., a pronunciation dictionary) at least partly based on the
adaptation result data (e.g., data showing that the word "cheese"
was pronounced differently during the speech-facilitated
transaction of ordering a western bacon cheese burger from an
automated drive-thru device, than the pronunciation dictionary
predicted).
[0208] Referring again to FIG. 11A, operation 708 may include
operation 1104 depicting monitoring the speech-facilitated
transaction between the particular party and the target device. For
example, FIG. 5, e.g., FIG. 5A, shows speech-facilitated
transaction between target device and particular party monitoring
module 504 monitoring (e.g., tracking a user mood regarding the
speech-facilitated transaction, e.g., frustrated, happy) the
speech-facilitated transaction (e.g., printing an airline ticket
for a trip to Wales) between the particular party (e.g., the user)
and the target device (e.g., an automated airline ticket dispensing
machine).
[0209] Referring again to FIG. 11A, operation 708 may include
operation 1106 depicting determining to modify the adaptation data
when the adaptation result data indicates that a success of the
speech-facilitated transaction is below a threshold level. For
example, FIG. 5, e.g., FIG. 5A, shows modification of adaptation
data determining based on adaptation result data indication of
success below threshold level module 506 determining to modify the
adaptation data (e.g., modify at least one parameter of an
algorithm used as a portion of the adaptation data, e.g., a phrase
completion algorithm) when the adaptation result data (e.g., a
success rate of the transaction measured by the target device
making measurements regarding success of interpreting speech)
indicates that a success of the speech-facilitated transaction
(e.g., controlling one or more systems of an automobile with
speech) is below a threshold level (e.g., the estimated success
rate drops below 60%).
[0210] Referring again to FIG. 11A, operation 1106 may include
operation 1108 depicting determining to modify the adaptation data
when a success rate of the speech-facilitated transaction is below
a threshold level. For example, FIG. 5, e.g., FIG. 5A, shows
modification of adaptation data determining based on threshold
level of success rate of speech-facilitated transaction module 508
determining to modify the adaptation data (e.g., changing an
algorithm selection parameter for the current conditions
surrounding the speech-facilitated transaction, e.g., microphone
quality and environmental noise) when a success rate of the
speech-facilitated transaction (e.g., an estimation of how many
spoken words are properly interpreted) is below a threshold level
(e.g., fifty percent).
[0211] Referring again to FIG. 11A, operation 1108 may include
operation 1110 depicting determining to modify the adaptation data
when a number of words that were not improperly interpreted during
the speech-facilitated transaction is below a threshold level. For
example, FIG. 5, e.g., FIG. 5A, shows modification of adaptation
data determining based on a number of words improperly interpreted
during speech-facilitated transaction below a threshold level
module 510 determining to modify the adaptation data (e.g.,
changing the regional dialect application algorithm) when a number
of words that were not improperly interpreted during the
speech-facilitated transaction is below a threshold level (e.g.,
when five words in a row have been improperly interpreted, or when
a proper interpretation rate drops below 55%).
[0212] Referring now to FIG. 11B, operation 708 may include
operation 1112 depicting modifying the adaptation data into
modified adaptation data at least partly based on the adaptation
result data. For example, FIG. 5, e.g., FIG. 5B, shows adaptation
data modifying at least partly based on adaptation result data
module 512 modifying the adaptation data (e.g., a phoneme
pronunciation database) into modified adaptation data (e.g.,
changing a pronunciation of one or more of the phonemes in the
phoneme pronunciation database) at least partly based on the
adaptation result data (e.g., data showing words containing a
particular phoneme were incorrectly interpreted one or more
times).
[0213] Referring again to FIG. 11B, operation 1112 may include
operation 1114 depicting modifying the adaptation data into
modified adaptation data at least partly based on the adaptation
result data, said adaptation data comprising a pronunciation
dictionary, and said adaptation result data comprising at least one
word that was improperly interpreted and a pronunciation of the at
least one word by the particular party. For example, FIG. 5, e.g.,
FIG. 5B, shows pronunciation dictionary modifying at least one word
at least partly based on received adaptation result data comprising
at least one word that was improperly interpreted and a
pronunciation of the at least one word by the particular party
module 514 modifying the adaptation data (e.g., a pronunciation
dictionary of one or more words) into modified adaptation data
(e.g., a pronunciation dictionary in which pronunciation of one or
more words is changed), said adaptation data comprising a
pronunciation dictionary, and said adaptation result data
comprising at least one word (e.g., "defrost") that was improperly
interpreted, and a pronunciation of the at least one word (e.g., in
the form of a sound made when the particular party uttered the word
"defrost," or a deconstruction of the particular party's
pronunciation of the word "defrost") by the particular party (e.g.,
the user).
[0214] Referring again to FIG. 11B, operation 1114 may include
operation 1116 depicting modifying the pronunciation dictionary of
the adaptation data into modified adaptation data by replacing a
pronunciation the at least one word that was improperly interpreted
with the pronunciation of the at least one word by the particular
party received as adaptation result data. For example, FIG. 5B
shows pronunciation dictionary replacing at least one word received
in adaptation result data with pronunciation received as adaptation
data module 516 modifying the pronunciation dictionary of the
adaptation data into modified adaptation data by replacing a
pronunciation of the at least one word (e.g., "forty") that was
improperly interpreted with the pronunciation of the at least one
word (e.g., "forty") by the particular party (e.g., the user)
received as adaptation result data (e.g., the adaptation result
data included the user's pronunciation of the word "forty").
[0215] FIGS. 12A-12B depict various implementations of operation
710, according to embodiments. Referring to FIG. 12A, operation 710
may include operation 1202 depicting facilitating transmission of
at least a portion of speech of the particular party that was
received as a portion of the adaptation result data. For example,
FIG. 6, e.g., FIG. 6A, shows at least a portion of a voice sample
received as a portion of the adaptation result data transmission to
receiving device facilitating module 602 facilitating transmission
(e.g., transmitting) of at least a portion of speech of the
particular party (e.g., the speech that the particular party used
to speak the word "fire the gun north" was received, processed, and
a processed version, e.g., a version in which the target device can
more easily process the speech, e.g., the background noise was
eliminated, and the accent of the particular party was adjusted
for) that was received as a portion of the adaptation result data
(e.g., the adaptation result data included some of the raw speech
data from the user).
[0216] Referring again to FIG. 12A, operation 710 may include
operation 1204 depicting facilitating transmission of at least a
portion of modified adaptation data to the receiving device,
wherein the receiving device is the target device. For example,
FIG. 6, e.g., FIG. 6A, shows at least a portion of modified
adaptation data transmission to target device as receiving device
facilitating module 604 facilitating transmission of (e.g.,
instructing a remote server to transmit) at least a portion of
modified adaptation data (e.g., a portion of a syllable
pronunciation database that had been modified in view of the
adaptation result data which suggested modification of syllable
pronunciation for more efficient user speech processing, based on
the syllable pronunciation spoken by the user during the
speech-facilitated transaction) to the receiving device (e.g., the
speech-enabled automated teller machine device), wherein the
receiving device (e.g., the speech-enabled automated teller machine
device) is the target device.
[0217] Referring again to FIG. 12A, operation 1204 may include
operation 1206 depicting facilitating transmission of modified
adaptation data to the target device, such that the modified
adaptation data is configured to be applied prior to completion of
the speech-facilitated transaction. For example, FIG. 6, e.g., FIG.
6A, shows at least a portion of modified adaptation data
transmission prior to completion of speech-facilitated transaction
facilitating module 606 facilitating transmission (e.g.,
transmitting) of modified adaptation data (e.g., changing of a
parameter of one or more of the algorithms used as adaptation data,
e.g., an accent-based pronunciation modification algorithm) to the
target device (e.g., a speech-input enabled vehicle control
system), such that the modified adaptation data (e.g., the
accent-based pronunciation modification algorithm with the changed
parameter) is configured to be applied (e.g., the speech will be
processed using the accent-based pronunciation modification
algorithm with the changed parameter) prior to completion of the
speech-facilitated transaction (e.g., controlling the temperature
inside a motor vehicle using speech).
[0218] Referring again to FIG. 12A, operation 1204 may include
operation 1208 depicting facilitating transmission of modified
adaptation data to the target device during the speech-facilitated
transaction. For example, FIG. 6, e.g., FIG. 6A, shows at least a
portion of modified adaptation data transmission to receiving
device during speech facilitated transaction facilitating module
608 facilitating transmission of modified adaptation data (e.g.,
using a different algorithm than what was transmitted previously as
adaptation data, e.g., the adaptation data included a basic
pronunciation adjustment algorithm, and the modified adaptation
data includes an utterance ignoring algorithm due to the adaptation
result data indicating a number of false positives) to the target
device (e.g., the automated drive-thru window) during the
speech-facilitated transaction (e.g., while the customer is still
attempting to place her order).
[0219] Referring again to FIG. 12A, operation 1204 may include
operation 1210 depicting facilitating transmission of modified
adaptation data to the target device, such that the modified
adaptation data is configured to be received prior to completion of
the speech-facilitated transaction. For example, FIG. 6, e.g., FIG.
6A, shows at least a portion of modified adaptation data configured
to be received prior to completion of speech-facilitated
transaction transmission facilitating module 610 facilitating
transmission of modified adaptation data (e.g., a different set of
proper noun pronunciations, because the proper noun pronunciations
sent in the adaptation data were not being used at a sufficiently
high rate to improve efficiency of the speech-facilitated
transaction), such that the modified adaptation data is configured
to be received prior to completion of the speech-facilitated
transaction (e.g., purchasing a train ticket from an automated
ticket dispensing device).
[0220] Referring again to FIG. 12A, operation 1204 may include
operation 1212 depicting facilitating transmission of modified
adaptation data to the target device, such that the modified
adaptation data is configured to be applied prior to completion of
the speech-facilitated transaction. For example, FIG. 6, e.g., FIG.
6A, shows at least a portion of modified adaptation data configured
to be applied prior to completion of speech-facilitated transaction
transmission facilitating module 612 facilitating transmission of
modified adaptation data (e.g., a modified sentence diagramming
path selection algorithm) to the target device (e.g., a speech
input-enabled DVD recorder), such that the modified adaptation data
(e.g., a sentence diagramming path selection algorithm with updated
path weights each time a command is given) is configured to be
applied prior to completion (e.g., before the user is finished
interacting) of the speech-facilitated transaction (e.g.,
programming the DVD recorder to record television shows).
[0221] Referring again to FIG. 12A, operation 710 may include
operation 1214 depicting facilitating transmission of modified
adaptation data to the receiving device, wherein the receiving
device is a device other than the target device. For example, FIG.
6, e.g., FIG. 6A shows at least a portion of modified adaptation
data transmission to device other than the target device
facilitating module 614 facilitating transmission of modified
adaptation data (e.g., an updated utterance ignoring algorithm with
a slightly modified threshold for identifying an ignorable
utterance) to the receiving device (e.g., a new speech-command
enabled television), wherein the receiving device (e.g., a
speech-command enabled television) is a device other than the
target device (e.g., which was an older speech-command enabled
television that has been replaced).
[0222] Referring now to FIG. 12B, operation 710 may include
operation 1216 depicting facilitating transmission of modified
adaptation data to the receiving device, wherein the receiving
device is a replacement of the target device. For example, FIG. 6,
e.g., FIG. 6B, shows at least a portion of modified adaptation data
transmission to a device that is a replacement for the target
device facilitating module 616 facilitating transmission of
modified adaptation data (e.g., a pronunciation dictionary with one
or more new words added based on the user speaking those words) to
the receiving device (e.g., a new home security system), wherein
the receiving device (e.g., the new home security system) is a
replacement of the target device (e.g., an older, outdated security
system from a different company, which, although outdated, the
speech recognition algorithms and training can be applied to the
new home security system).
[0223] Referring again to FIG. 12B, operation 710 may include
operation 1218 depicting facilitating transmission of modified
adaptation data to the receiving device, which is connected to the
target device via a network. For example, FIG. 6, e.g., FIG. 6B,
shows at least at least a portion of modified adaptation data
transmission to receiving device connected to the target device via
a network facilitating module 618 facilitating transmission of
modified adaptation data (e.g., an updated phrase completion
algorithm) to the receiving device (e.g., a portable tablet
device), that is connected to the target device (e.g., a home
computer) via a network (e.g., a local area network provided by a
router operating in the house).
[0224] Referring again to FIG. 12B, operation 710 may include
operation 1220 depicting facilitating transmission of modified
adaptation data to the receiving device, which is configured to
communicate via a same network as the target device. For example,
FIG. 6, e.g., FIG. 6B, shows at least a portion of modified
adaptation data transmission to receiving device communicating on a
same network as the target device facilitating module 620
facilitating transmission of modified adaptation data (e.g., a
pronunciation dictionary) to the receiving device (e.g., a
speech-enabled copier/scanner machine on a separate floor of an
office building), that is configured to communicate via a same
network (e.g., a company intranet) as the target device (e.g., the
user's work computer where the user dictates her word processing,
and then goes down to the copier to have copies made of the
documents she generates).
[0225] Referring again to FIG. 12B, operation 710 may include
operation 1222 depicting facilitating transmission of modified
adaptation data to the receiving device, which is configured to
perform a same function as the target device. For example, FIG. 6,
e.g., FIG. 6B, shows at least a portion of modified adaptation data
transmission to receiving device configured to perform a same
function as the target device facilitating module 622 facilitating
transmission of modified adaptation data (e.g., a noise level
dependent filtration algorithm with a parameter changed) to the
receiving device (e.g., a new speech input-enabled television),
that is configured to perform a same function (e.g., playing
television) as the target device (e.g., an Apple TV with
speech-enabled input).
[0226] Referring again to FIG. 12B, operation 710 may include
operation 1224 depicting facilitating transmission of modified
adaptation data to the receiving device, which is a same type as
the target device. For example, FIG. 6, e.g., FIG. 6B, shows at
least a portion of modified adaptation data transmission to
receiving device of a same type as the target device facilitating
module 624 facilitating transmission of modified adaptation data
(e.g., a modified pronunciation dictionary, modified to increase a
counter showing how many times each word's pronunciation has been
looked up) to the receiving device (e.g., the motor vehicle with an
in-vehicle voice command system), which is a same type as the
target device (e.g., a different motor vehicle that the user
previously owned).
[0227] Referring now to FIG. 12C, operation 710 may include
operation 1226 depicting transmitting modified adaptation data from
a particular device to the receiving device. For example, FIG. 6,
e.g., FIG. 6C, shows modified adaptation data transmitting from
particular device to receiving device module 626 transmitting
modified adaptation data (e.g., a pronunciation dictionary in which
a counter indicating how many times the pronunciation dictionary
was used has been incremented as a modification to the adaptation
data) from a particular device (e.g., a user's smartphone) to the
receiving device (e.g., a speech-enabled automated teller machine
device).
[0228] Referring again to FIG. 12C, operation 1226 may include
operation 1228 depicting transmitting modified adaptation data from
a particular device configured to communicate on a same network as
the receiving device. For example, FIG. 6, e.g., FIG. 6C, shows
modified adaptation data transmitting from particular device
configured to communicate on a same network as the receiving device
module 628 transmitting modified adaptation data (e.g., a regional
dialect application algorithm) from a particular device (e.g., a
user's home computer) configured to communicate on a same network
(e.g., a home network set up by a personal router connected to a
Wide Area Network) as the receiving device (e.g., a speech enabled,
integrated home theater system).
[0229] Referring again to FIG. 12C, operation 1226 may include
operation 1230 depicting transmitting modified adaptation data from
a particular device configured to communicate with both of the
target device and the receiving device, to the receiving device.
For example, FIG. 6, e.g., FIG. 6C, shows modified adaptation data
transmitting from particular device configured to communicate with
receiving device and target device module 630 transmitting modified
adaptation data (e.g., a phrase completion algorithm with different
path weights) from a particular device (e.g., a USB stick carried
by a company worker, used to transmit adaptation data and/or other
credentials to company property) configured to communicate with
both of the target device (e.g., the company worker's regular
computer in her office) and the receiving device (e.g., a check-out
laptop available to company employees), to the receiving device
(e.g., the check-out laptop).
[0230] Referring again to FIG. 12C, operation 1226 may include
operation 1232 depicting transmitting modified adaptation data
stored on the particular device to the receiving device. For
example, FIG. 6, e.g., FIG. 6C, shows modified adaptation data
stored on particular device transmitting from particular device to
receiving device module 632 transmitting modified adaptation data
(e.g., a syllable pronunciation database with updated
pronunciations) stored on the particular device (e.g., a video game
controller with a memory and a transmit/receive function) to the
receiving device (e.g., a video game system).
[0231] Referring again to FIG. 12C, operation 710 may include
operation 1234 depicting facilitating transmission of the
adaptation data as the portion of the modified adaptation data,
wherein the adaptation data is modified by incrementing a counter
configured to count usage of the adaptation data. For example, FIG.
6, e.g., FIG. 6C, shows adaptation data, said adaptation data
modified by incrementing a counter, as at least a portion of
modified adaptation data transmission to receiving device
facilitating module 634 facilitating transmission of the adaptation
data (e.g., an accent-based pronunciation modification algorithm)
as the portion of the modified adaptation data (e.g., the
accent-based pronunciation modification algorithm is what is
transferred, but the modified adaptation result data also includes
a counter), wherein the adaptation data is modified by incrementing
a counter configured to count usage (e.g., how many times the
algorithm is selected and/or used) of the adaptation data (e.g.,
the accent-based pronunciation modification algorithm).
[0232] Referring again to FIG. 12C, operation 710 may include
operation 1236 depicting facilitating transmission of at least a
portion of modified adaptation data to a receiving device, wherein
the modified adaptation data is different than the adaptation data.
For example, FIG. 6, e.g., FIG. 6C, shows at least a portion of
modified adaptation data, said modified adaptation data different
than the adaptation data, transmission to receiving device
facilitating module 636 facilitating transmission of at least a
portion of modified adaptation data (e.g., particular words of a
pronunciation dictionary) to a receiving device (e.g., a portable
navigation system), wherein the modified adaptation data (e.g.,
particular words of a pronunciation dictionary) is different than
the adaptation data (e.g., different words are chosen, although no
words had a pronunciation change).
[0233] Referring again to FIG. 12C, operation 710 may include
operation 1238 depicting facilitating transmission of at least a
portion of modified adaptation data to a receiving device, wherein
the modified adaptation data is based on the adaptation result
data. For example, FIG. 6, e.g., FIG. 6C, shows at least a portion
of modified adaptation data based on the adaptation data
transmission to receiving device facilitating module 638
facilitating transmission of at least a portion of modified
adaptation data (e.g., a list of one or more parameters to change
in the speech processing algorithm) to a receiving device (e.g., a
speech-enabled Blu-ray player), wherein the modified adaptation
data (e.g., the list of parameters to change) is based on the
adaptation result data (e.g., the result of the speech processing
was used to determine which parameters to change, e.g., if heavy
vowel words were taking longer to process, then a parameter for
processing those words would be modified).
[0234] Referring now to FIG. 12D, operation 710 may include
operation 1240 depicting facilitating transmission of at least a
portion of modified adaptation data to a receiving device, wherein
the modified adaptation data comprises at least a portion of the
adaptation result data. For example, FIG. 6, e.g., FIG. 6D, shows
at least a portion of modified adaptation data, said modified
adaptation data including at least a portion of the adaptation
result data, transmission to receiving device facilitating module
640 facilitating transmission (e.g., transmitting) of at least a
portion of modified adaptation data (e.g., a pronunciation
dictionary with a changed pronunciation of at least one word) to a
receiving device (e.g., to a speech-enabled video game system),
wherein the modified adaptation data (e.g., the pronunciation
dictionary with a changed word pronunciation) comprises at least a
portion (e.g., the changed pronunciation) of the adaptation result
data (e.g., the adaptation result data included the way that the
user was pronouncing the word "money," and that pronunciation was
used to modify the adaptation data to change the pronunciation of
the word "money" in the pronunciation dictionary to the way that
the user most recently spoke the word "money" to the target
device).
[0235] Referring again to FIG. 12D, operation 710 may include
operation 1242 depicting facilitating transmission of at least a
portion of modified adaptation data to a receiving device, wherein
the modified adaptation data is at least partially based on
applying the adaptation result data to the adaptation data. For
example, FIG. 6, e.g., FIG. 6D, shows at least a portion of
modified adaptation data, said modified adaptation data at least
partially based on applying the adaptation result data,
transmission to receiving device facilitating module 642
facilitating transmission (e.g., carrying out one or more actions
to assist in transmitting, e.g., providing an address, e.g., an IP
address, of the receiving device, so that data can be transmitted
by a different device, e.g., a remote server with a web address, to
the receiving device) of at least a portion of modified adaptation
data (e.g., a phrase completion algorithm with modified path
weights) to a receiving device (e.g., an automated teller machine
device), wherein the modified adaptation data is at least partially
based on applying the adaptation result data (e.g., a statistical
analysis of which paths of the phrase completion algorithm led to
high confidence of successful interpretation rates) to the
adaptation data (e.g., the statistical analysis of the most
effective paths is used to increase the path weights of the most
effective paths in the phrase completion algorithm).
[0236] The foregoing detailed description has set forth various
embodiments of the devices and/or processes via the use of block
diagrams, flowcharts, and/or examples. Insofar as such block
diagrams, flowcharts, and/or examples contain one or more functions
and/or operations, it will be understood by those within the art
that each function and/or operation within such block diagrams,
flowcharts, or examples can be implemented, individually and/or
collectively, by a wide range of hardware, software, firmware, or
virtually any combination thereof. In one embodiment, several
portions of the subject matter described herein may be implemented
via Application Specific Integrated Circuitry (ASICs), Field
Programmable Gate Arrays (FPGAs), digital signal processors (DSPs),
or other integrated formats. However, those skilled in the art will
recognize that some aspects of the embodiments disclosed herein, in
whole or in part, can be equivalently implemented in integrated
circuitry, as one or more computer programs running on one or more
computers (e.g., as one or more programs running on one or more
computer systems), as one or more programs running on one or more
processors (e.g., as one or more programs running on one or more
microprocessors), as firmware, or as virtually any combination
thereof, and that designing the circuitry and/or writing the code
for the software and or firmware would be well within the skill of
one of skill in the art in light of this disclosure. In addition,
those skilled in the art will appreciate that the mechanisms of the
subject matter described herein are capable of being distributed as
a program product in a variety of forms, and that an illustrative
embodiment of the subject matter described herein applies
regardless of the particular type of signal bearing medium used to
carry out the distribution. Examples of a signal bearing medium
include, but are not limited to, the following: a recordable type
medium such as a floppy disk, a hard disk drive, a Compact Disc
(CD), a Digital Video Disk (DVD), a digital tape, a computer
memory, etc.; and a transmission type medium such as a digital
and/or an analog communication medium (e.g., a fiber optic cable, a
waveguide, a wired communications link, a wireless communication
link, etc.).
[0237] Alternatively or additionally, implementations may include
executing a special-purpose instruction sequence or invoking
circuitry for enabling, triggering, coordinating, requesting, or
otherwise causing one or more occurrences of virtually any
functional operations described herein. In some variants,
operational or other logical descriptions herein may be expressed
as source code and compiled or otherwise invoked as an executable
instruction sequence. In some contexts, for example,
implementations may be provided, in whole or in part, by source
code, such as C++, or other code sequences. In other
implementations, source or other code implementation, using
commercially available and/or techniques in the art, may be
compiled//implemented/translated/converted into a high-level
descriptor language (e.g., initially implementing described
technologies in C or C++ programming language and thereafter
converting the programming language implementation into a
logic-synthesizable language implementation, a hardware description
language implementation, a hardware design simulation
implementation, and/or other such similar mode(s) of expression).
For example, some or all of a logical expression (e.g., computer
programming language implementation) may be manifested as a
Verilog-type hardware description (e.g., via Hardware Description
Language (HDL) and/or Very High Speed Integrated Circuit Hardware
Descriptor Language (VHDL)) or other circuitry model which may then
be used to create a physical implementation having hardware (e.g.,
an Application Specific Integrated Circuit). Those skilled in the
art will recognize how to obtain, configure, and optimize suitable
transmission or computational elements, material supplies,
actuators, or other structures in light of these teachings.
[0238] In a general sense, those skilled in the art will recognize
that the various aspects described herein which can be implemented,
individually and/or collectively, by a wide range of hardware,
software, firmware, or any combination thereof can be viewed as
being composed of various types of "electrical circuitry."
Consequently, as used herein "electrical circuitry" includes, but
is not limited to, electrical circuitry having at least one
discrete electrical circuit, electrical circuitry having at least
one integrated circuit, electrical circuitry having at least one
application specific integrated circuit, electrical circuitry
forming a general purpose computing device configured by a computer
program (e.g., a general purpose computer configured by a computer
program which at least partially carries out processes and/or
devices described herein, or a microprocessor configured by a
computer program which at least partially carries out processes
and/or devices described herein), electrical circuitry forming a
memory device (e.g., forms of random access memory), and/or
electrical circuitry forming a communications device (e.g., a
modem, communications switch, or optical-electrical equipment).
Those having skill in the art will recognize that the subject
matter described herein may be implemented in an analog or digital
fashion or some combination thereof.
[0239] Those having skill in the art will recognize that it is
common within the art to describe devices and/or processes in the
fashion set forth herein, and thereafter use engineering practices
to integrate such described devices and/or processes into data
processing systems. That is, at least a portion of the devices
and/or processes described herein can be integrated into a data
processing system via a reasonable amount of experimentation. Those
having skill in the art will recognize that a typical data
processing system generally includes one or more of a system unit
housing, a video display device, a memory such as volatile and
non-volatile memory, processors such as microprocessors and digital
signal processors, computational entities such as operating
systems, drivers, graphical user interfaces, and applications
programs, one or more interaction devices, such as a touch pad or
screen, and/or control systems including feedback loops and control
motors (e.g., feedback for sensing position and/or velocity;
control motors for moving and/or adjusting components and/or
quantities). A typical data processing system may be implemented
utilizing any suitable commercially available components, such as
those typically found in data computing/communication and/or
network computing/communication systems.
[0240] Those skilled in the art will recognize that it is common
within the art to implement devices and/or processes and/or
systems, and thereafter use engineering and/or other practices to
integrate such implemented devices and/or processes and/or systems
into more comprehensive devices and/or processes and/or systems.
That is, at least a portion of the devices and/or processes and/or
systems described herein can be integrated into other devices
and/or processes and/or systems via a reasonable amount of
experimentation. Those having skill in the art will recognize that
examples of such other devices and/or processes and/or systems
might include--as appropriate to context and application--all or
part of devices and/or processes and/or systems of (a) an air
conveyance (e.g., an airplane, rocket, helicopter, etc.), (b) a
ground conveyance (e.g., a car, truck, locomotive, tank, armored
personnel carrier, etc.), (c) a building (e.g., a home, warehouse,
office, etc.), (d) an appliance (e.g., a refrigerator, a washing
machine, a dryer, etc.), (e) a communications system (e.g., a
networked system, a telephone system, a Voice over IP system,
etc.), (f) a business entity (e.g., an Internet Service Provider
(ISP) entity such as Comcast Cable, Qwest, Southwestern Bell,
etc.), or (g) a wired/wireless services entity (e.g., Sprint,
Cingular, Nextel, etc.), etc.
[0241] In certain cases, use of a system or method may occur in a
territory even if components are located outside the territory. For
example, in a distributed computing context, use of a distributed
computing system may occur in a territory even though parts of the
system may be located outside of the territory (e.g., relay,
server, processor, signal-bearing medium, transmitting computer,
receiving computer, etc. located outside the territory)
[0242] The herein described subject matter sometimes illustrates
different components contained within, or connected with, different
other components. It is to be understood that such depicted
architectures are merely exemplary, and that in fact many other
architectures can be implemented which achieve the same
functionality. In a conceptual sense, any arrangement of components
to achieve the same functionality is effectively "associated" such
that the desired functionality is achieved. Hence, any two
components herein combined to achieve a particular functionality
can be seen as "associated with" each other such that the desired
functionality is achieved, irrespective of architectures or
intermediate components. Likewise, any two components so associated
can also be viewed as being "operably connected", or "operably
coupled", to each other to achieve the desired functionality, and
any two components capable of being so associated can also be
viewed as being "capable of being operably coupled", to each other
to achieve the desired functionality. Specific examples of operably
coupled include but are not limited to physically mateable and/or
physically interacting components and/or wirelessly interactable
and/or wirelessly interacting components and/or logically
interacting and/or logically interactable components.
[0243] Those skilled in the art will recognize that at least a
portion of the devices and/or processes described herein can be
integrated into a data processing system. Those having skill in the
art will recognize that a data processing system generally includes
one or more of a system unit housing, a video display device,
memory such as volatile or non-volatile memory, processors such as
microprocessors or digital signal processors, computational
entities such as operating systems, drivers, graphical user
interfaces, and applications programs, one or more interaction
devices (e.g., a touch pad, a touch screen, an antenna, etc.),
and/or control systems including feedback loops and control motors
(e.g., feedback for sensing position and/or velocity; control
motors for moving and/or adjusting components and/or quantities). A
data processing system may be implemented utilizing suitable
commercially available components, such as those typically found in
data computing/communication and/or network computing/communication
systems
[0244] While particular aspects of the present subject matter
described herein have been shown and described, it will be apparent
to those skilled in the art that, based upon the teachings herein,
changes and modifications may be made without departing from the
subject matter described herein and its broader aspects and,
therefore, the appended claims are to encompass within their scope
all such changes and modifications as are within the true spirit
and scope of the subject matter described herein. Furthermore, it
is to be understood that the invention is defined by the appended
claims.
[0245] It will be understood by those within the art that, in
general, terms used herein, and especially in the appended claims
(e.g., bodies of the appended claims) are generally intended as
"open" terms (e.g., the term "including" should be interpreted as
"including but not limited to," the term "having" should be
interpreted as "having at least," the term "includes" should be
interpreted as "includes but is not limited to," etc.). It will be
further understood by those within the art that if a specific
number of an introduced claim recitation is intended, such an
intent will be explicitly recited in the claim, and in the absence
of such recitation no such intent is present. For example, as an
aid to understanding, the following appended claims may contain
usage of the introductory phrases "at least one" and "one or more"
to introduce claim recitations. However, the use of such phrases
should not be construed to imply that the introduction of a claim
recitation by the indefinite articles "a" or "an" limits any
particular claim containing such introduced claim recitation to
inventions containing only one such recitation, even when the same
claim includes the introductory phrases "one or more" or "at least
one" and indefinite articles such as "a" or "an" (e.g., "a" and/or
"an" should typically be interpreted to mean "at least one" or "one
or more"); the same holds true for the use of definite articles
used to introduce claim recitations.
[0246] In addition, even if a specific number of an introduced
claim recitation is explicitly recited, those skilled in the art
will recognize that such recitation should typically be interpreted
to mean at least the recited number (e.g., the bare recitation of
"two recitations," without other modifiers, typically means at
least two recitations, or two or more recitations). Furthermore, in
those instances where a convention analogous to "at least one of A,
B, and C, etc." is used, in general such a construction is intended
in the sense one having skill in the art would understand the
convention (e.g., "a system having at least one of A, B, and C"
would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C
together, and/or A, B, and C together, etc.).
[0247] In those instances where a convention analogous to "at least
one of A, B, or C, etc." is used, in general such a construction is
intended in the sense one having skill in the art would understand
the convention (e.g., "a system having at least one of A, B, or C"
would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C
together, and/or A, B, and C together, etc.). It will be further
understood by those within the art that virtually any disjunctive
word and/or phrase presenting two or more alternative terms,
whether in the description, claims, or drawings, should be
understood to contemplate the possibilities of including one of the
terms, either of the terms, or both terms. For example, the phrase
"A or B" will be understood to include the possibilities of "A" or
"B" or "A and B."
[0248] With respect to the appended claims, those skilled in the
art will appreciate that recited operations therein may generally
be performed in any order. In addition, although various
operational flows are presented in a sequence(s), it should be
understood that the various operations may be performed in other
orders than those that are illustrated, or may be performed
concurrently. Examples of such alternate orderings may include
overlapping, interleaved, interrupted, reordered, incremental,
preparatory, supplemental, simultaneous, reverse, or other variant
orderings, unless context dictates otherwise. Furthermore, terms
like "responsive to," "related to," or other past-tense adjectives
are generally not intended to exclude such variants, unless context
dictates otherwise.
[0249] Those skilled in the art will appreciate that the foregoing
specific exemplary processes and/or devices and/or technologies are
representative of more general processes and/or devices and/or
technologies taught elsewhere herein, such as in the claims filed
herewith and/or elsewhere in the present application.
* * * * *
References