U.S. patent application number 17/119563 was filed with the patent office on 2021-04-01 for sequence dependent data message consolidation in a voice activated computer network environment.
This patent application is currently assigned to Google LLC. The applicant listed for this patent is Google LLC. Invention is credited to Gaurav Bhaya, Robert James Stets, JR..
Application Number | 20210099511 17/119563 |
Document ID | / |
Family ID | 1000005266370 |
Filed Date | 2021-04-01 |
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United States Patent
Application |
20210099511 |
Kind Code |
A1 |
Bhaya; Gaurav ; et
al. |
April 1, 2021 |
SEQUENCE DEPENDENT DATA MESSAGE CONSOLIDATION IN A VOICE ACTIVATED
COMPUTER NETWORK ENVIRONMENT
Abstract
Systems and methods to combine multiple voice activated audio
input data packets that indicate sequence dependent operations are
provided. A natural language processor component can receive first
and second input audio signal from a client computing device, and
can identify respective requests and corresponding trigger
keywords. A direct action application programming interface ("API")
can generate respective action data structures, and can construct
respective data transmissions including the respective action data
structures. A thread optimization component can obtain data packets
of the first data transmission, and can obtain data packets of the
second data transmission. The thread optimization component can
determine, based on a heuristic technique applied to the data
packets of the respective data transmissions a sequence dependency
parameter. The thread optimization component can merge, based on a
comparison of the sequence dependency parameter with a threshold,
the first and second data transmissions into a single thread.
Inventors: |
Bhaya; Gaurav; (Sunnyvale,
CA) ; Stets, JR.; Robert James; (Mountain View,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google LLC |
Mountain View |
CA |
US |
|
|
Assignee: |
Google LLC
Mountain View
CA
|
Family ID: |
1000005266370 |
Appl. No.: |
17/119563 |
Filed: |
December 11, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16818736 |
Mar 13, 2020 |
10893088 |
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17119563 |
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15395725 |
Dec 30, 2016 |
10630751 |
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16818736 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L 67/10 20130101;
H04L 67/327 20130101; G06F 16/951 20190101; G06F 40/279 20200101;
G06F 16/90332 20190101; H04L 67/02 20130101; G10L 15/26
20130101 |
International
Class: |
H04L 29/08 20060101
H04L029/08; G06F 16/951 20060101 G06F016/951; G06F 16/9032 20060101
G06F016/9032; G10L 15/26 20060101 G10L015/26; G06F 40/279 20060101
G06F040/279 |
Claims
1.-20. (canceled)
21. A system to perform sequence dependent operations in a
voice-based computing environment, comprising: a data processing
system comprising memory and one or more processors to: receive
data packets comprising one or more input audio signals detected by
a sensor of a client computing device; parse the one or more input
audio signals to identify one or more requests and one or more
keywords corresponding to the one or more requests; generate, based
on the one or more keywords, a first action data structure and a
second action data structure; determine a sequence dependency
parameter for the first action data structure and the second action
data structure; combine, based on the sequence dependency
parameter, the first action data structure and the second action
data structure into a single thread comprising a series of sequence
dependent actions; select a content item for at least one action in
the series of sequence dependent actions; and provide the content
item to the client computing device.
22. The system of claim 21, comprising: the data processing system
to combine, based on a comparison of the sequence dependency
parameter with a threshold, the first action data structure and the
second action data structure into the single thread.
23. The system of claim 21, comprising the data processing system
to: construct a first data transmission including the first action
data structure to establish a first communication session between a
first service provider computing device and the client computing
device.
24. The system of claim 23, comprising: the data processing system
to merge, based on a comparison of the sequence dependency
parameter with a threshold, the first data transmission with a
second data transmission of the second action data structure into
the single thread.
25. The system of claim 21, comprising the data processing system
to: generate the first action data structure responsive to receipt
of a first input audio signal of the one or more input audio
signals; and generate the second action data structure responsive
to receipt of a second input audio signal of the one or more input
audio signals.
26. The system of claim 21, comprising: the data processing system
to generate the first action data structure and the second action
data structure based on a first input audio signal of the one or
more input audio signals.
27. The system of claim 21, comprising the data processing system
to: establish, responsive to the first action data structure, a
first communication session between a first service provider
computing device and the client computing device; and establish,
responsive to the second action data structure, a second
communication session between a second service provider computing
device and the client computing device.
28. The system of claim 21, comprising the data processing system
to: detect a completion of a first action of the first action data
structure; and transmit data packets of the single thread to a
service provider computing device subsequent to the completion of
the first action, wherein the single thread indicates that the
first action is scheduled to occur prior to a second action of the
second action data structure.
29. The system of claim 21, wherein the sequence dependency
parameter indicates that an action corresponding to the first
action data structure is scheduled to occur prior to an action
corresponding to the second action data structure.
30. The system of claim 21, comprising the data processing system
to: identify a condition associated with the second action data
structure based on a time associated with the first action data
structure; and prevent transmission of data packets of the second
action data structure to a service provider computing device
responsive to the condition.
31. The system of claim 21, wherein the single thread indicates the
series of sequence dependent actions for the single thread, the
series of sequence dependent actions including a first action, a
second action subsequent to the first action, and a third action
subsequent to the second action.
32. A method of performing sequence dependent operations in a
voice-based computing environment, comprising: receiving, by one or
more processors, data packets comprising one or more input audio
signals detected by a sensor of a client computing device; parsing,
by the one or more processors, the one or more input audio signals
to identify one or more requests and one or more keywords
corresponding to the one or more requests; generating, by the one
or more processors, based on the one or more keywords, a first
action data structure and a second action data structure;
determining, by the one or more processors, a sequence dependency
parameter for the first action data structure and the second action
data structure; combining, by the one or more processors based on
the sequence dependency parameter, the first action data structure
and the second action data structure into a single thread
comprising a series of sequence dependent actions; selecting, by
the one or more processors, a content item for at least one action
in the series of sequence dependent actions; and providing, by the
one or more processors, the content item to the client computing
device.
33. The method of claim 32, comprising: combining, by the one or
more processors based on a comparison of the sequence dependency
parameter with a threshold, the first action data structure and the
second action data structure into the single thread.
34. The method of claim 32, comprising: constructing, by the one or
more processors, a first data transmission including the first
action data structure to establish a first communication session
between a first service provider computing device and the client
computing device.
35. The method of claim 34, comprising: merging, by the one or more
processors, based on a comparison of the sequence dependency
parameter with a threshold, the first data transmission with a
second data transmission of the second action data structure into
the single thread.
36. The method of claim 32, comprising: generating, by the one or
more processors, the first action data structure responsive to
receipt of a first input audio signal of the one or more input
audio signals; and generating, by the one or more processors, the
second action data structure responsive to receipt of a second
input audio signal of the one or more input audio signals.
37. The method of claim 32, comprising: generating, by the one or
more processors, the first action data structure and the second
action data structure based on a first input audio signal of the
one or more input audio signals.
38. The method of claim 32, comprising: establishing, by the one or
more processors, responsive to the first action data structure, a
first communication session between a first service provider
computing device and the client computing device; and establishing,
by the one or more processors, responsive to the second action data
structure, a second communication session between a second service
provider computing device and the client computing device.
39. The method of claim 32, comprising: detecting, by the one or
more processors, a completion of a first action of the first action
data structure; and transmitting, by the one or more processors,
data packets of the single thread to a service provider computing
device subsequent to the completion of the first action, wherein
the single thread indicates that the first action is scheduled to
occur prior to a second action of the second action data
structure.
40. The method of claim 32, wherein the sequence dependency
parameter indicates that an action corresponding to the first
action data structure is scheduled to occur prior to an action
corresponding to the second action data structure.
Description
CROSS-REFERENCES TO RELATED APPLICATIONS
[0001] This application claims the benefit of priority under 35
U.S.C. .sctn. 120 as a continuation of U.S. patent application Ser.
No. 16/818,736, filed Mar. 13, 2020, which claims the benefit of
priority under 35 U.S.C. .sctn. 120 as a continuation of U.S.
patent application Ser. No. 15/395,725, filed Dec. 30, 2016, each
of which is hereby incorporated by reference herein in its
entirety.
BACKGROUND
[0002] Excessive network transmissions, packet-based or otherwise,
of network traffic data between computing devices can prevent a
computing device from properly processing the network traffic data,
completing an operation related to the network traffic data, or
timely responding to the network traffic data. The excessive
network transmissions of network traffic data can also complicate
data routing or degrade the quality of the response if the
responding computing device is at or above its processing capacity,
which may result in inefficient bandwidth utilization. The control
of network transmissions corresponding to content item objects can
be complicated by the large number of content item objects that can
initiate network transmissions of network traffic data between
computing devices.
SUMMARY
[0003] At least one aspect is directed to a system to combine
multiple voice activated audio input data packets that indicate
sequence dependent operations. A natural language processor
component executed by a data processing system can receive, via an
interface of the data processing system, data packets comprising a
first input audio signal detected by a sensor of a client computing
device. The natural language processor component can parse the
first input audio signal to identify a first request and a first
trigger keyword corresponding to the first request. A direct action
application programming interface ("API") of the data processing
system can generate, based on the first trigger keyword and in
response to the first request, a first action data structure. The
direct action API can construct a first data transmission including
the first action data structure to establish a first communication
session between a first service provider computing device and the
client computing device, data packets of the first communication
session routed from the client computing device to the first
service provider computing device via the data processing system.
The natural language processor component can receive, via the
interface of the data processing system, data packets comprising a
second input audio signal detected by the sensor of the client
computing device, and can parse the second input audio signal to
identify a second request and a second trigger keyword
corresponding to the second request. The direct action API can
generate, based on the second trigger keyword and in response to
the second request, a second action data structure. The direct
action API can construct a second data transmission including the
second action data structure to establish a second communication
session between a second service provider computing device and the
client computing device, data packets of the second communication
session routed from the client computing device to the second
service provider computing device via the data processing system. A
thread optimization component executed by the data processing
system can obtain data packets of the first data transmission, and
can obtain data packets of the second data transmission. The thread
optimization component can determine, based on a heuristic
technique applied to the data packets of the first data structure
and the data packets applied to the second data structure, a
sequence dependency parameter. The thread optimization component
can merge, based on a comparison of the sequence dependency
parameter with a threshold, the first data transmission with the
second action data transmission into a single thread.
[0004] At least one aspect is directed to a method of managing
multiple voice activated audio input data communications that
indicate sequence dependent operations. The method can include
receiving, by a natural language processor component executed by a
data processing system, via an interface of the data processing
system, data packets comprising a first input audio signal detected
by a sensor of a client computing device. The method can include
identifying, by the natural language processor component, from the
first input audio signal, a first request and a first trigger
keyword corresponding to the first request. The method can include
generating, by a direct action application programming interface
("API") of the data processing system, based on the first trigger
keyword and in response to the first request, a first action data
structure. The method can include constructing a first data
transmission including the first action data structure for a first
communication session between a first service provider computing
device and the client computing device, data packets of the first
communication session routed from the client computing device to
the first service provider computing device via the data processing
system. The method can include receiving, by the natural language
processor component, via the interface of the data processing
system, data packets comprising a second input audio signal
detected by the sensor of the client computing device, and parsing,
by the natural language processor component, the second input audio
signal to identify a second request and a second trigger keyword
corresponding to the second request. The method can include
generating, by the direct action API, based on the second trigger
keyword and in response to the second request, a second action data
structure. The method can include constructing a second data
transmission including the second action data structure for a
second communication session between a second service provider
computing device and the client computing device, data packets of
the second communication session routed from the client computing
device to the second service provider computing device via the data
processing system. The method can include obtaining, by a thread
optimization component executed by the data processing system, data
of the first data transmission, and data of the second data
transmission. The method can include determining, based on a
heuristic technique applied to the data of the first data
transmission and applied to the data of the second data
transmission, a sequence dependency parameter. The method can
include associating, based on a comparison of the sequence
dependency parameter with a threshold, the first action data
structure and the second action data structure with a single
thread.
[0005] At least one aspect is directed to a computer readable
storage medium storing instructions that when executed by one or
more data processors, cause the one or more data processors to
perform operations to manage multiple voice activated audio input
data communications that indicate sequence dependent operations.
The operations can include receiving, by a natural language
processor component executed by a data processing system, via an
interface of the data processing system, data packets comprising a
first input audio signal detected by a sensor of a client computing
device. The operations can include identifying, by the natural
language processor component, from the first input audio signal, a
first request and a first trigger keyword corresponding to the
first request. The operations can include generating, by a direct
action application programming interface ("API") of the data
processing system, based on the first trigger keyword and in
response to the first request, a first action data structure. The
operations can include constructing a first data transmission
including the first action data structure for a first communication
session between a first service provider computing device and the
client computing device, data packets of the first communication
session routed from the client computing device to the first
service provider computing device via the data processing system.
The operations can include receiving, by the natural language
processor component, via the interface of the data processing
system, data packets comprising a second input audio signal
detected by the sensor of the client computing device, and parsing,
by the natural language processor component, the second input audio
signal to identify a second request and a second trigger keyword
corresponding to the second request. The operations can include
generating, by the direct action API, based on the second trigger
keyword and in response to the second request, a second action data
structure. The operations can include constructing a second data
transmission including the second action data structure for a
second communication session between a second service provider
computing device and the client computing device, data packets of
the second communication session routed from the client computing
device to the second service provider computing device via the data
processing system. The operations can include obtaining, by a
thread optimization component executed by the data processing
system, data packets of the first data transmission, and data
packets of the second data transmission. The operations can include
determining, based on a heuristic technique applied to the data
packets of the first data structure and the data packets applied to
the second data structure, a sequence dependency parameter. The
operations can include associating, based on the sequence
dependency parameter, the first action data structure and the
second action data structure with a single thread.
[0006] These and other aspects and implementations are discussed in
detail below. The foregoing information and the following detailed
description include illustrative examples of various aspects and
implementations, and provide an overview or framework for
understanding the nature and character of the claimed aspects and
implementations. The drawings provide illustration and a further
understanding of the various aspects and implementations, and are
incorporated in and constitute a part of this specification.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] The accompanying drawings are not intended to be drawn to
scale. Like reference numbers and designations in the various
drawings indicate like elements. For purposes of clarity, not every
component may be labeled in every drawing. In the drawings:
[0008] FIG. 1 depicts a system to combine multiple voice activated
audio input data packets that indicated sequence dependent
operations in a voice activated computer network environment;
[0009] FIG. 2 depicts a functional diagram of a single thread
structure for a voice activated data packet based computer network
environment;
[0010] FIG. 3 depicts a functional diagram of thread data structure
generation and communication between remote data processing systems
and service provider computing devices in a voice activated data
packet based computer network environment;
[0011] FIG. 4 depicts method to manage multiple voice activated
audio input data communications that indicate sequence dependent
operations; and
[0012] FIG. 5 is a block diagram illustrating a general
architecture for a computer system that may be employed to
implement elements of the systems and methods described and
illustrated herein.
DETAILED DESCRIPTION
[0013] Following below are more detailed descriptions of various
concepts related to, and implementations of, methods, apparatuses,
and systems to optimize processing of multiple voice activated
audio input data packets in a voice activated computer network
environment. The various concepts introduced above and discussed in
greater detail below may be implemented in any of numerous
ways.
[0014] Systems and methods of the present disclosure relate
generally to a data processing system that optimizes or dynamically
adjusts multiple voice activated packet (or other protocol) based
input audio signals via packet based transmissions in a voice
activated computer network environment. The data processing system
can improve the efficiency and effectiveness of data packet
transmission over one or more computer networks by, for example,
extracting information from input audio signals to generate
multiple corresponding action data structures. The action data
structures can be constructed for transmission during communication
sessions between the data processing system and multiple different
service provider computing devices. From, for example, the packets
of different action data structures, the data processing system can
determine at least one sequence dependency parameter. The sequence
dependency parameters can indicate an order of operation of actions
indicated by the action data structures or their corresponding data
transmissions. Based on the sequence dependency parameters, the
data processing system can merge or combine multiple action data
transmissions into a single thread.
[0015] The single thread can include sequence dependent operations
of multiple action data structures. The data processing system can
provide the single thread or portions thereof (e.g., at least one
packet based data structure) to multiple service provider computing
devices to accomplish actions indicated by the single thread. The
data processing system can also provide the single thread or
portions thereof to at least one content provider computing device
to obtain content items associated with the single thread. The
service provider computing devices and the content provider
computing devices can communicate, via or bypassing the data
processing system, with at least one client computing device (e.g.,
a source of the audio input signals) to render audio output to
accomplish the actions indicated by the thread, or to render
content items at the client computing device.
[0016] By merging or otherwise consolidating multiple action data
structures into a single thread, and by identifying sequence
dependent operations indicated by the single thread, the
processing, power, and memory utilization requirements of the data
processing system are reduced, relative to individual processing of
multiple action data structures without such consolidation and
sequence dependency identification. For example, asynchronous or
out-of-sequence processing of operations of individual action data
structures can cause untimely, premature, or unnecessary data
packet communications via established communication sessions
between the data processing system and the service provider or
content provider computing devices. This wastes bandwidth, and can
cause unnecessary processing operations to occur by the data
processing system as well as by the service provider or content
provider computing devices, which wastes computing resources of
multiple computing devices.
[0017] Based on identified sequence dependent operations in the
single thread, the data processing system can temporarily or
permanently skip initial operations of a set of sequence dependent
operations and can instead proceed to an operation that corresponds
to a later-in-time or final operation. By bypassing packet or other
protocol based data transmissions that correspond to an early
operation of a plurality of sequence dependent operations, and
instead proceeding directly to packet based data transmissions for
later stage operations in a sequence of operations the data
processing system can reduce, delay, or eliminate data processing
associated with the early stage operations. This saves processing
power and other computing resources such as memory, reduces
electrical power consumption by the data processing system and the
reduced data transmissions via the computer network reduces
bandwidth requirements and usage of the data processing system.
[0018] The systems and methods described herein can include a data
processing system that receives a first input audio signal. From
the first input audio signal, the data processing system can
identify a first request and a first trigger keyword corresponding
to the request. Based on the first trigger keyword or the first
request, the data processing system can generate a first action
data structure, and can construct or prepare a first data
transmission including the first action data structure. The first
data transmission can be routed as a data packet or other protocol
based transmission from the client computing device to at least one
first service provider computing device as part of a first
communication session.
[0019] The data processing system can receive a second input audio
signal. From the second input audio signal, the data processing
system can identify a second request and a second trigger keyword
corresponding to the request. Based on the second trigger keyword
or the second request, the data processing system can generate a
second action data structure, and can construct or prepare a second
data transmission including the second action data structure. The
second data transmission can be routed as a data packet or other
protocol based transmission from the client computing device to at
least one second service provider computing device as part of a
second communication session. The first and second service provider
computing devices can correspond to different entities that do not
communicate with each other via the data processing system.
[0020] The data processing system can obtain data packets of the
first and second transmissions (e.g., from the first and second
data structures) and can extract information from the data packets
to determine at least one sequence dependency parameter. The
sequence dependency parameter can indicate a sequence of operations
for actions of the first and second data structures. The data
processing system can compare the sequence dependency parameter to
a threshold (e.g., a rule, policy, or value) and based on the
comparison the data processing system can merge the first and
second data transmissions (or associated action data structures)
into a single thread. The single thread can indicate actions of the
first and second (or more) action data structures, and can indicate
a sequence or order of these actions, as well as sequence
dependencies where for example a second action cannot (or is not
scheduled to) begin until after a first action is complete.
[0021] The data processing system can reorder, skip, or at least
temporarily bypass operations related to some actions of the single
thread, based for example on sequence dependencies or based on
input received from the client computing device. This can be done
before or without performing at least some of the data processing
operations based on the bypassed action. Bypassing the processing
operations for a first action can cause data related to a second
action to identified, transmitted and rendered with less data
processing and less electrical power usage than would be the case
without the bypass.
[0022] FIG. 1 depicts an example system 100 to optimize processing
of multiple action data structures having sequence dependent
operations in a voice activated data packet (or other protocol)
based computer network environment. The system 100 can include at
least one data processing system 105, for example as part of a
voice activated communication or planning system. The data
processing system 105 can include at least one server having at
least one processor. For example, the data processing system 105
can include a plurality of servers located in at least one data
center or server farm. The data processing system 105 can
determine, from an audio input signal a request and a trigger
keyword associated with the request. Based on the request and
trigger keyword the data processing system 105 can generate an
action data structure. The action data structure can indicate at
least one action that corresponds to the input audio signal. The
data processing system 105 can receive multiple separate input
audio signals, and for each input audio signal can create a
respective data structure. The data processing system 105 can
construct or otherwise prepare data transmissions for each data
structure to transmit the data structures during respective
communication sessions with respective other computing devices
(e.g., servicer provider computing devices or content provider
computing devices). The data processing system 105 can determine,
from the action data structures or corresponding data
transmissions, one or more sequence dependency parameter. Based on
the sequence dependency parameter, the data processing system 105
can merge multiple data transmissions (or corresponding action data
structures) into a single thread. The single thread can indicate
actions from at least two action data structures, as well as orders
of operations or sequence dependencies of the actions.
[0023] The data processing system 105 can include multiple,
logically-grouped servers and facilitate distributed computing
techniques. The logical group of servers may be referred to as a
data center, server farm or a machine farm. The servers can be
geographically dispersed. A data center or machine farm may be
administered as a single entity, or the machine farm can include a
plurality of machine farms. The servers within each machine farm
can be heterogeneous--one or more of the servers or machines can
operate according to one or more type of operating system platform.
The data processing system 105 can include servers in a data center
that are stored in one or more high-density rack systems, along
with associated storage systems, located for example in an
enterprise data center. The data processing system 105 with
consolidated servers in this way can improve system manageability,
data security, the physical security of the system, and system
performance by locating servers and high performance storage
systems on localized high performance networks. Centralization of
all or some of the data processing system 105 components, including
servers and storage systems, and coupling them with advanced system
management tools allows more efficient use of server resources,
which saves power and processing requirements and reduces bandwidth
usage.
[0024] The data processing system 105 can include at least one
natural language processor (NLP) component 110, at least one
interface 115, at least one thread optimization component 120, at
least one content selector component 125, at least one audio signal
generator component 130, at least one direct action application
programming interface (API) 135, at least one session handler
component 140, and at least one data repository 145. The NLP
component 110, interface 115, thread optimization component 120,
content selector component 125, audio signal generator component
130, direct action API 135, and session handler component 140 can
each include at least one processing unit, server, virtual server,
circuit, engine, agent, appliance, or other logic device such as
programmable logic arrays configured to communicate with the data
repository 145 and with other computing devices (e.g., the client
computing device 150, the content provider computing device 155, or
the service provider computing device 160) via the at least one
computer network 165. The network 165 can include computer networks
such as the internet, local, wide, metro or other area networks,
intranets, satellite networks, other computer networks such as
voice or data mobile phone communication networks, and combinations
thereof.
[0025] The network 165 can include or constitute a display network,
e.g., a subset of information resources available on the internet
that are associated with a content placement or search engine
results system, or that are eligible to include third party content
items as part of a content item placement campaign. The network 165
can be used by the data processing system 105 to access information
resources such as web pages, web sites, domain names, or uniform
resource locators that can be presented, output, rendered, or
displayed by the client computing device 150. For example, via the
network 165 a user of the client computing device 150 can access
information or data provided by the content provider computing
device 155 or the service provider computing device 160.
[0026] The network 165 can include, for example a point-to-point
network, a broadcast network, a wide area network, a local area
network, a telecommunications network, a data communication
network, a computer network, an ATM (Asynchronous Transfer Mode)
network, a SONET (Synchronous Optical Network) network, a SDH
(Synchronous Digital Hierarchy) network, a wireless network or a
wireline network, and combinations thereof. The network 165 can
include a wireless link, such as an infrared channel or satellite
band. The topology of the network 165 may include a bus, star, or
ring network topology. The network 165 can include mobile telephone
networks using any protocol or protocols used to communicate among
mobile devices, including advanced mobile phone protocol ("AMPS"),
time division multiple access ("TDMA"), code-division multiple
access ("CDMA"), global system for mobile communication ("GSM"),
general packet radio services ("GPRS") or universal mobile
telecommunications system ("UMTS"). Different types of data may be
transmitted via different protocols, or the same types of data may
be transmitted via different protocols.
[0027] The client computing device 150, the content provider
computing device 155, and the service provider computing device 160
can each include at least one logic device such as a computing
device having a processor to communicate with each other or with
the data processing system 105 via the network 165. The client
computing device 150, the content provider computing device 155,
and the service provider computing device 160 can each include at
least one server, processor or memory, or a plurality of
computation resources or servers located in at least one data
center. The client computing device 150, the content provider
computing device 155, and the service provider computing device 160
can each include at least one computing device such as a desktop
computer, laptop, tablet, personal digital assistant, smartphone,
portable computer, server, thin client computer, virtual server, or
other computing device.
[0028] The client computing device 150 can include at least one
sensor 151, at least one transducer 152, at least one audio driver
153, and at least one speaker 154. The sensor 151 can include a
microphone or audio input sensor. The transducer 152 can convert
the audio input into an electronic signal. The audio driver 153 can
include a script or program executed by one or more processors of
the client computing device 150 to control the sensor 151, the
transducer 152 or the audio driver 153, among other components of
the client computing device 150 to process audio input or provide
audio output. The speaker 154 can transmit the audio output
signal.
[0029] The client computing device 150 can be associated with an
end user that enters voice queries as audio input into the client
computing device 150 (via the sensor 151) and receives audio output
in the form of a computer generated voice that can be provided from
the data processing system 105 (or the content provider computing
device 155 or the service provider computing device 160) to the
client computing device 150, output from the speaker 154. The
computer generated voice can include recordings from a real person
or computer generated language.
[0030] The content provider computing device 155 can provide audio
based content items for display by the client computing device 150
as an audio output content item. The content item can include an
offer for a good or service, such as a voice based message that
states: "Would you like me to order you a taxi?" For example, the
content provider computing device 155 can include memory to store a
series of audio content items that can be provided in response to a
voice based query. The content provider computing device 155 can
also provide audio based content items (or other content items) to
the data processing system 105 where they can be stored in the data
repository 145. The data processing system 105 can select the
content items that include an audio component and provide (or
instruct the content provider computing device 155 to provide) the
content items to the client computing device 150. The audio based
content items can be exclusively audio or can be combined with
text, image, or video data. The content items can include one or
more audio files that when rendered provide an audio output or
acoustic wave. The content items can include other content (e.g.,
text, video, or image content) in addition to or instead of audio
content. For example the content items can include text or image
files, or combinations thereof, that do not include audio files and
that do not render audio output.
[0031] The service provider computing device 160 can include at
least one service provider natural language processor (NLP)
component 161 and at least one service provider interface 162. The
service provider NLP component 161 (or other components such as a
direct action API of the service provider computing device 160) can
engage with the client computing device 150 (via the data
processing system 105 or bypassing the data processing system 105)
to create a back-and-forth real-time voice or audio based
conversation (e.g., a session) between the client computing device
150 and the service provider computing device 160. For example, the
service provider interface 162 can receive or provide data messages
to the direct action API 135 of the data processing system 105. The
service provider computing device 160 and the content provider
computing device 155 can be associated with the same entity. For
example, the content provider computing device 155 can create,
store, or make available content items for a car sharing service,
and the service provider computing device 160 can establish a
session with the client computing device 150 to arrange for a
delivery of a taxi or car of the car share service to pick up the
end user of the client computing device 150. The data processing
system 105, via the direct action API 135, the NLP component 110 or
other components can also establish the session with the client
computing device 150, including or bypassing the service provider
computing device 160, to arrange for example for a delivery of a
taxi or car of the car share service.
[0032] The data repository 145 can include one or more local or
distributed databases, and can include a database management
system. The data repository 145 can include computer data storage
or memory and can store one or more parameters 146, one or more
policies 147, content data 148, or templates 149 among other data.
The parameters 146, policies 147, and templates 149 can include
information such as rules about a voice based session between the
client computing device 150 (or the service provider computing
device 160) and the data processing system 105. The content data
148 can include content items for audio output or associated
metadata, as well as input audio messages that can be part of one
or more communication sessions with the client computing device
150.
[0033] The data processing system 105 can include an application,
script or program installed at the client computing device 150,
such as an app to communicate input audio signals to the interface
115 of the data processing system 105 and to drive components of
the client computing device to render output audio signals. The
data processing system 105 can receive data packets or other signal
that includes or identifies an audio input signal. For example, the
data processing system 105 can execute or run at least part of the
NLP component 110 to receive the audio input signal.
[0034] The NLP component 110 can convert the audio input signal
into recognized text by comparing the input signal against a
stored, representative set of audio waveforms (e.g., in the data
repository 145) and choosing the closest matches. The
representative waveforms are generated across a large set of users,
and can be augmented with speech samples. After the audio signal is
converted into recognized text, the NLP component 110 can match the
text to words that are associated, for example via training across
users or through manual specification, with actions that the data
processing system 105 can serve.
[0035] The audio input signal can be detected by the sensor 151
(e.g., a microphone) of the client computing device. Via the
transducer 152, the audio driver 153, or other components the
client computing device 150 can provide the audio input signal to
the data processing system 105 (e.g., via the network 165) where it
can be received (e.g., by the interface 115) and provided to the
NLP component 110 or stored in the data repository 145 as content
data 148.
[0036] The system 100 can optimize processing of action data
structures that include sequence dependent operations in a voice
activated data packet (or other protocol) environment. For example,
the data processing system 105 can include or be part of a voice
activated assistant service, voice command device, intelligent
personal assistant, knowledge navigator, event planning, or other
assistant program. The data processing system 105 can provide one
or more instances of audio output for display from the client
computing device 150 to accomplish tasks related to this input
audio signal. The tasks can include, for example, communicating
with the service provider computing device 160 or other third party
computing devices to make dinner reservations or purchase movie
tickets. For example, an end user can enter an input audio signal
into the client computing device 150 of: "OK, I would like to go to
go dinner tonight." This input audio signal can be detected by the
sensor 151 (e.g., a microphone) of the client computing device 150
and transformed (e.g., by the transducer 152) into a data packet or
other protocol based structure for transmission to the data
processing system 105.
[0037] The NLP component 110 can receive or otherwise obtain at
least one first input audio signal. For example, via the interface
115 and the computer network 165 the NLP component 110 can obtain
the first input audio signal from the client computing device 150.
The NLP component 110 can extract data from or otherwise parse the
first input audio signal to identify at least one first request or
at least one first trigger keyword corresponding to the first
request. The first request can indicate intent or subject matter of
the first input audio signal, e.g., an intent to eat dinner. The
first trigger keyword can indicate a type of action likely to be
taken. For example, the NLP component 110 can parse the first input
audio signal to identify at least one request to leave home for the
evening for dinner. The first trigger keyword can include at least
one word, phrase, root or partial word, or derivative indicating an
action to be taken. For example, the trigger keyword "go" or "to go
to" from the input audio signal can indicate a need for transport.
In this example, the input audio signal (or the identified request)
does not directly express an intent for transport, however the
trigger keyword indicates that transport is an ancillary or
sub-action to at least one other action that is indicated by the
request.
[0038] The NLP component 110 can receive a second input audio
signal. For example, the first audio input signal can be "OK, I
would like to go to go dinner tonight" and the second audio input
signal can be "OK, I would like to catch a movie later". The NLP
component 110 can receive or otherwise obtain the second input
audio signal from any client computing device 150, in an analogous
manner to which the first input audio signal was obtained, e.g.,
via the network 165. The NLP component 110 can extract data from or
otherwise parse the second input audio signal to identify at least
one second request or at least one second trigger keyword
corresponding to the second request. The second request can
indicate intent or subject matter of the second input audio signal,
e.g., an intent to watch a movie in a theater. The second trigger
keyword can indicate a type of action likely to be taken. For
example, the NLP component 110 can parse the second input audio
signal to identify at least one request to leave home for the
evening to watch a movie. The second trigger keyword can include at
least one word, phrase, root or partial word, or derivative
indicating an action to be taken. For example, the trigger keyword
"to catch" from the second input audio signal can indicate a need
for transport, e.g., as an ancillary or sub-action to at least one
other action that is indicated by the request.
[0039] The direct action API 135 can execute programs or scripts,
for example from the NLP component 110, the thread optimization
component 120, or the content selector component 125 to perform
tasks or actions, or to identify content items responsive to input
audio signals. The direct action API 135 can execute a specified
action to satisfy the end user's intention, as determined by the
data processing system 105. Depending on the action specified in
its inputs, the direct action API 135 can execute code or a dialog
script that identifies the parameters required to fulfill a user
request. Such code can lookup additional information, e.g., in the
data repository 145, such as the name of a home automation service,
or it can provide audio output for rendering at the client
computing device 150 to ask the end user questions such as the
intended destination of a requested taxi, genre of a movie to
watch, or type of restaurant to go to for dinner. The direct action
API 135 can determine necessary parameters and can package the
information into an action data structure, which can then be sent
to another component such as the content selector component 125 or
to the service provider computing device 160 (or content provider
computing device 155) to be fulfilled.
[0040] The direct action API 135 of the data processing system 105
can generate, based on the request or the trigger keyword, data
structures for the actions of the thread. The action data
structures can be generated responsive to the request. The action
data structure can be included in the messages that are transmitted
to or received by the service provider computing device 160. Based
on the request parsed by the NLP component 110, the direct action
API 135 can determine to which of a plurality of service provider
computing devices 160 the message should be sent.
[0041] The direct action API 135 can generate a first action data
structure based on the first trigger keyword and in response to the
first request, and can generate a second action data structure
based on the second trigger keyword and in response to the second
request. For example, if the first input audio signal includes "go
to dinner tonight" the NLP component 110 can identify the trigger
word "tonight" and the request for a dinner suggestion or
reservation. The direct action API 135 can package the request into
a first action data structure for transmission as a message to a
service provider computing device 160 (or content provider
computing device 155) of a restaurant. The first input audio signal
can include other requests or trigger keywords that indicate other
actions, ancillary to the dinner action. These actions can be
included in the first action data structure. For example, the NLP
component 110 can identify first requests or first trigger keywords
for transportation to or from dinner (additional actions) from the
first input audio signal of "OK, I would like to go to go dinner
tonight".
[0042] If, for example the second input audio signal includes
"catch a movie later" the NLP component 110 can identify the
request to see a movie with the trigger keywords "catch" or
"later". The direct action API 135 can package the request into a
second action data structure for transmission as a message to a
service provider computing device 160 (or content provider
computing device 155) of a movie company or movie theater. The
second input audio signal can include other second requests or
second trigger keywords that indicate other actions, ancillary to
the movie action. These actions can be included in the second
action data structure. For example, the NLP component 110 can
identify first requests or first trigger keywords for
transportation to or from a movie theater (additional actions) from
the second input audio signal of "OK, I would like to catch a movie
later".
[0043] The first and second, or any other action data structures
can also be passed to the content selector component 125. The
action data structures can include information for completing one
or more actions associated with the request. In this example, the
information can include restaurant or movie interest indicators,
location information, an identification or location of a restaurant
or type of restaurant, restaurant reservation information, movie
show times at a theater, theater location information, or a pick up
location and a destination location. The direct action API 135 can
retrieve a template 149 from the repository 145 to determine which
fields to include in the action data structure. The direct action
API 135 can retrieve content from the repository 145 to obtain
information for the fields of the data structure. The direct action
API 135 can populate the fields from the template with that
information to generate the data structure. The direct action API
135 can also populate the fields with data from the input audio
signal or third party sources. The templates 149 can be
standardized for categories of service providers or can be
standardized for specific service providers. For example, ride
sharing service providers can use the following standardized
template 149 to create the data structure:
{client_device_identifier; authentication_credentials;
pick_up_location; destination_location; no_passengers;
service_level}. The data structure can include variable fields. The
variable fields can indicate, for example, a sequence or order of
operation of multiple actions identified indicated by or related to
at least one action of a data structure. The direct action API 135
can populate fields of the data structure, including variable
fields. The direct action API 135 can populate or enter data into
one or more variable fields of a data structure based on a sequence
dependency between actions, such as a second action that begins
after a first action ends.
[0044] The direct action API 135 can construct data transmissions
that include data packets corresponding to action data structures.
For example, the data transmissions can include packetized versions
of the action data structures, e.g., data packets with header and
payload regions that indicate information represented by the data
structures. The data transmissions can be used to establish (e.g.,
take part in) at least one communication session between the
service provider computing device 160 and the client computing
device 150 via the data processing system 105. The session handler
component 140 can establish or identify the communication sessions
via the interface 115. For example, subsequent to merging or
associating action first and second data structures (or their
corresponding packetized data transmissions) into a single thread,
the data processing system 105 can provide the data transmissions
to the service provider computing device 160. As part of the
communications of the communication session, the service provider
computing device 160 can also receive, via the data processing
system 105, data packets (or other data messages) from the client
computing device 105. For example, the data processing system 105
can receive and can route inbound data messages from the client
computing device 150 to the service provider computing device 160
as part of the communication session.
[0045] The thread optimization component 120 can obtain or access
data packets of the first and second (and any other) data
transmissions. For example, the direct action API 135 can provide
the transmissions (e.g., the corresponding data packets) to the
data repository 145 for storage, where they can be retrieved by the
thread optimization component 120. The thread optimization
component 120 can also receive the data packets (or other protocol
based structure) of the data transmissions from the direct action
API 135 (or other data processing system 105 component) bypassing
the data repository 145.
[0046] The thread optimization component 120 can parse or otherwise
extract information from data packets of multiple data
transmissions that correspond respectively to multiple action data
structures. For example, the thread optimization component 120 can
apply a heuristic technique to data packets of a first data
transmission (or to the corresponding first data structure) and to
data packets of a second data transmission (or to the corresponding
second data structure) to determine at least one sequence
dependency parameter. The heuristic or other statistical technique
can determine or identify with a threshold degree of certainty
patterns among the first and second data transmissions (or
corresponding data structures) that indicate a sequence dependency
of actions indicated by the data transmissions.
[0047] The sequence dependency parameter can indicate the existence
or likelihood (e.g., relative to a threshold level or other
benchmark) of actions represented by the data transmissions (or
corresponding action data structures) having an order of
operations, time, or sequence dependency on each other. The
sequence dependent operations or actions, indicated by the sequence
dependency parameters, can include a number of actions that occur
in a known, suggested, required, or particular order. For example,
going from home to a movie theater, then back home can include
three sequence dependent operations or actions. The first action in
this example includes travelling from home to the movie theater.
The second action includes watching the movie in the theater. The
third action includes returning home from the theater.
[0048] These three (and perhaps other) actions can be determined by
the direct action API 135 from requests or trigger keywords
corresponding to the input audio signal "OK, I would like to catch
a movie later". In this example, the second action in the sequence
(watching the movie) is subsequent to and dependent on the first
action (going out from home to the movie theater), and the third
action (returning home) is subsequent to and dependent on the first
action and the second action. The third action can be considered
subsequent to and dependent on the second action, as having
expressed an intent to do so, the data processing system 105
determines or predicts that the end user would watch the movie in
the theater before returning home as well.
[0049] Based on the sequence dependency parameter, the thread
optimization component 120 can merge two or more packetized data
transmissions (or their corresponding action data structures) into
a single thread. The single thread can include data identifying
actions as well as other data (e.g., metadata or third party data)
from multiple data action structures. The single thread can be in
packetized (or other protocol based) form, e.g., in the same format
as the first and second data transmissions. The single thread can
also be in a data structure format, e.g., generated by the direct
action API 135, or following a format of at least one template 149,
policy 147, or parameter 146. The single thread can include or
indicate an association or linking of actions from one or more data
transmissions, or from one or more action data structures.
[0050] The data transmissions or action data structures can be
merged or otherwise associated with one another by the thread
optimization component 120 to generate the single thread prior to
transmission of the data indicated by the action data structures
via the communication session to the service provider computing
device 160. In this example, the direct action API 135 or other
data processing system 105 component (e.g., the interface 115) can
transmit at least part of the data indicated by the single thread,
subsequent to the merger or creation of the single thread, to the
service provider computing device 160 for the first time. For
example, prior to creation of the single thread, the data
processing system 105 may have delayed, prevented withheld, or not
transmitted data associated with the first or second (or any other)
data structure. In some examples, at least some of the data
indicated by individual data structures can be provided by and from
the data processing system 105 to the service provider computing
device 160 prior to creation of the single thread.
[0051] The thread optimization component 120 can merge or otherwise
consolidate or associate the data transmissions (or corresponding
action data structures) into the single thread based on the
sequence dependency parameter. For example, the first data
transmission (and first data structure) can represent actions
associated with the first input audio signal "OK, I would like to
go to go dinner tonight" the second data transmission (and second
data structure) can represent actions associated with the second
input audio signal "OK, I would like to catch a movie later". The
first and second (or any other) input audio signals can be
sequential (following on another by less than one minute),
separated from one another by time (e.g., greater than one minute),
and can originate from the same or different client computing
devices 150. The thread optimization component 120 can obtain data
packets (or other data) representing this information, and can
determine at least one sequence dependency parameter. For example,
the sequence dependency parameter can indicate that the action of
returning home from the movie theater occurs after the action of
watching the movie, or that the action of watching the movie occurs
or is predicted to occur after the action of eating dinner.
[0052] The single thread (in any data structure or format) can
indicate a set of sequence dependent operations that correspond to
one or more input audio signals (or corresponding data structures
or data transmissions), such as a series of actions. The thread can
include any two or more actions, such as a first action, a second
action, and a third action. For example, a merger of the first
input audio signal "OK, I would like to go to go dinner tonight,"
and the second input audio signal "OK, I would like to catch a
movie later" can include at least one request indicating an
interest to attend dinner and a movie, and at least one trigger
keyword, e.g., "go" indicating a need for transportation. The
thread optimization component 120 can identify at least one
sequence dependency parameter indicating at least one sequence,
temporal, or order of operations dependency between the actions and
can generate the single thread to combine the multiple input audio
signals (or corresponding template based data structures or
packet/protocol based data transmissions). The thread optimization
component 120 can create the single thread that indicates at least
three actions, such as a dinner action (first action), a movie
action (second action), and a transportation home action (third
action). In this example, from the requests or the trigger keywords
the thread optimization component 120 generates a single thread
from multiple separate inputs that indicates the three actions. The
single thread can include other actions, such as an initial
transport to dinner action.
[0053] The data processing system 105 or component thereof such as
the thread optimization component 120 can determine that the
actions of the thread are sequence dependent operations. For
example, the thread optimization component can determine that the
second action of watching the movie is subsequent to the first
action of eating dinner, and that the third action of travelling
home from the movie theater is after the second action of watching
the movie. The thread optimization component 120 can access the
parameters 146 or policies 147 in the data repository 145 to
determine or otherwise estimate the order of the sequence dependent
actions. For example, the parameters 146 or policies 147 could
indicate that a transport action (e.g., a taxi home) can occur
after an event action (e.g., watching a movie).
[0054] The content selector component 125 can obtain indications of
any of the actions of the single thread. For example, the thread
optimization component 120 can directly or indirectly (e.g., via
the data repository 145) provide at least a portion of the single
thread that indicates the third (or any other) action to the
content selector component 125. The content selector component 125
can obtain this information from the data repository 145, where it
can be stored as part of the content data 148. The indication of
the third action can inform the content selector component 125 of a
need for transportation from the location of the movie theater to a
location as determined or indicated by the client computing device
150, such as a ride to an end destination.
[0055] The content selector component 125 can obtain indications of
a later action in the thread prior to the occurrence of at least
one earlier action. For example, the content selector component 125
can receive an indication of the third action (e.g., a need for a
ride from the movie theater) before the movie plays in the theater
(second action), or before the person who input the input audio
signal into the client computing device 150 eats dinner at the
restaurant (first action). The content selector component 125 can
obtain indications of at least one action of the thread before
completion of at least one action of the thread.
[0056] From the information received by the content selector
component 125, e.g., an indication of the third action before
occurrence of at least one prior action in the sequence dependent
thread, the content selector component 125 can identify at least
one content item. The content item can be responsive or related to
the third (or any other) action. For example, the content item can
include an audio message offering services of a car share company,
responsive to the third action that indicates a transportation
need. The content selector component 125 can query the data
repository 145 to select or otherwise identify the content item,
e.g., from the content data 148. The content selector component 125
can also select the content item from the content provider
computing device 155. For example responsive to a query received
from the data processing system 105, the content provider computing
device 155 can provide a content item to the data processing system
105 (or component thereof) for eventual output by the client
computing device 150.
[0057] The audio signal generator component 130 can generate or
otherwise obtain an output signal that includes the content item
responsive to the third (or any other) action. For example, the
data processing system 105 can execute the audio signal generator
component to generate or create an output signal corresponding to
the content item. The interface 115 of the data processing system
105 can provide or transmit one or more data packets that include
the output signal via the computer network 165 to the client
computing device 150, e.g., as part of the communication session.
The interface 115 can be designed, configured, constructed, or
operational to receive and transmit information using, for example,
data packets. The interface 115 can receive and transmit
information using one or more protocols, such as a network
protocol. The interface 115 can include a hardware interface,
software interface, wired interface, or wireless interface. The
interface 115 can facilitate translating or formatting data from
one format to another format. For example, the interface 115 can
include an application programming interface that includes
definitions for communicating between various components, such as
software components of the system 100.
[0058] For example the data processing system 105 can provide the
output signal from the data repository 145 or from the audio signal
generator component 130 to the client computing device 150. The
data processing system 105 can also instruct, via data packet
transmissions, the content provider computing device 155 or the
service provider computing device 160 to provide the output signal
to the client computing device 150. The output signal can be
obtained, generated, transformed to or transmitted as one or more
data packets (or other communications protocol) from the data
processing system 105 (or other computing device) to the client
computing device 150.
[0059] The content selector component 125 can skip to a later
action in a set of sequence dependent operations indicated by the
single thread to select a content item for the later action prior
to occurrence (and prior to an immediate need) for activity
corresponding to the later action. By skipping to a later sequenced
action, e.g., to select a content item for the second subsequent
action prior to selecting a content item for a first prior action,
the data processing system 105 is not required to first process
information related to the prior action to select content items for
subsequent actions. This reduces processor utilization, power
consumption and bandwidth from data transmissions that would
otherwise be associated with selecting a content item (for the
first action) prior to selecting the content item for the second
action.
[0060] The content selector component 125 can select the content
item for the (subsequent or later) action as part of a real-time
content selection process. For example, the content item can be
provided to the client computing device for transmission as audio
output in a conversational manner in direct response to the input
audio signal. The real-time content selection process to identify
the content item and provide the content item to the client
computing device 150 can occur within one minute or less from the
time of the input audio signal and be considered real-time.
[0061] The output signal that corresponds to the content item
corresponding to the content provider computing device 155 (or data
corresponding to the service provider computing device 160), for
example obtained or generated by the audio signal generator
component 130 transmitted via the interface 115 and the computer
network 165 to the client computing device 150, can cause the
client computing device 150 to execute the audio driver 153 to
drive the speaker 154 to generate an acoustic wave corresponding to
the output signal. The acoustic wave can include words of or
corresponding to the content item or other data for the later,
(e.g., second or third) action. The output signal that corresponds
to the content item can also include non-audio content items that
render on the client computing device 150 that is the source of the
input audio signal or on a different client computing device 150
(e.g., a wearable device computing device) as text or image
messages that can render without audio elements.
[0062] The data processing system 105 can provide the output signal
that includes the content item or other data responsive to an
action in direct or real-time response to the input audio signal so
that the packet based data transmissions via the computer network
165 that are part of a communication session between the data
processing system 105 and the client computing device 150 has the
flow and feel of a real-time person to person conversation. This
packet based data transmission communication session can also
include the content provider computing device 155 or the service
provider computing device 160.
[0063] The content selector component 125 can select content items
provided in response to the second (or any non-first) action in the
sequence dependent set of actions before selecting any content item
for any prior action in the sequence. This avoids the need to
process at least some of the data corresponding to the prior
actions, which causes the second content item to be selected with a
reduced number of processing operations than would occur if the
content items were selected in an order that matches the order of
the sequence of actions. Content items for the prior (e.g., first
and second) actions may or may not be selected, for example after
selection of the content item for the second action.
[0064] The content selector component 125 can select the content
item (e.g., for the second action) based on at least one trigger
keyword of the thread that indicates subject matter different than
subject matter of the one or more requests of the same thread. For
example, the requests of the single thread can indicate subject
matter of a dinner request (first action), and subject matter of a
movie request (second action). This subject matter does not
indicate any transportation request. However, the NLP component 110
or the thread optimization component 120 (or other data processing
system 105 components executing as part of the direct action API
135) can identify the trigger keyword "go" "go to" or "to go to"
and can determine a transportation request based at least in part
on the trigger keyword. Thus, the data processing system 105 can
infer actions from the input audio signal that are secondary
requests that are not the primary request or subject of the input
audio signal.
[0065] The data processing system 105 can prevent or delay
transmission of the output signal that includes the content item.
For example, the interface 115 or a script executing via the direct
action API 135 can prevent transmission of data packets that
include the output signal corresponding to a content item or to an
action of the single thread until a triggering event. The
triggering event can include expiration of a pre-determined time
period, such as two hours or a time coinciding with occurrence of
an earlier action in the thread, such as a scheduled end time of a
movie. The triggering event can also include an authorization
indication received by the data processing system 105 from the
client computing device 150. The authorization indication can
originate as a subsequent audio input associated with the thread
but received by the data processing system 105 subsequent to the
input audio signal, a text-based or other non-audible signal, or
can include an indication of a setting of the client computing
device 150 that authorizes receipt by the client computing device
150 of content items.
[0066] The data processing system 105 can also delay transmission
of the content item associated with a second or subsequent to
second action of the thread to optimize processing utilization. For
example, the data processing system 105 can delay content item
transmission until an off-peak or non-peak period of data center
usage, which results in more efficient utilization of the data
center by reducing peak bandwidth usage, heat output or cooling
requirements. The data processing system 105 can also initiate a
conversion or other activity associated with the content item, such
as ordering a car service, based on data center utilization rates
or bandwidth metrics or requirements of the network 165 or of a
data center that includes the data processing system 105.
[0067] The content items can correspond to the actions of the
thread, and the content selector component 125 can select a content
item for one, more than one, or all actions of the thread. The
thread optimization component 120 can identify the sequence
dependent thread of actions of, for example, "dinner" (first
action) "movie" (second action) and "transport from movie location"
(third action).
[0068] For example, based on the single thread, the content item
for the third action can be provided for rendering at the client
computing device 150 as an audio response that states "Would you
like a ride home from the movie theater?" in response to the audio
input signal. Subsequent or prior to this rendering, the data
processing system 105 can select or provide a content item, e.g.,
"the Italian restaurant downtown has an opening for 7 pm
tonight--are you interested?" for the first action (dinner), and
can select or provide another content item, e.g., "would you like
tickets to the 9 pm movie at the downtown theater?" for the second
action (movie). The data processing system 105 can provide (which
includes instructing the content provider computing device 155 to
provide) these content items responsive to the input audio signal
for rendering by the client computing device 150 as audio output
content items. The data processing system 105, via the interface
115, can select or provide these content items in any order to the
client computing device 150. For example, the content item for the
third (e.g., last) action can be selected or provided first, before
content items corresponding to other, earlier actions of the
thread.
[0069] The data processing system 105 can receive a response to the
content item "would you like a ride home from the movie theater?"
The response can include an input audio signal, e.g., "yes please"
that was entered into the client computing device 150 by the end
user and received by the data processing system 105. The data
processing system 105 or component thereof (e.g., the thread
optimization component) can include the response as part of the
single thread. Based on this response, the direct action API 135
can communicate with the service provider computing device 160
(that can be associated with the content item, such as a car share
company) to order a taxi or ride share vehicle for the location of
the movie theater at the time the movie ends. The data processing
system 105 can obtain this location or time information as part of
the data packet (or other protocol) based data message
communication with the client computing device 150, from the data
repository 145, or from other sources such as the service provider
computing device 160 or the content provider computing device 155.
Confirmation of this order (or other conversion) can be provided as
an audio communication from the data processing system 105 to the
client computing device 150 in the form of an output signal from
the data processing system 105 that drives the client computing
device 150 to render audio output such as, "great, you will have a
car waiting for you at 11 pm outside the theater." The data
processing system 105, via the direct action API 135, can
communicate with the service provider computing device 160 to
confirm the order for the car.
[0070] The data processing system 105 can obtain the response
(e.g., "yes please") to the content item ("would you like a ride
home from the movie theater?") and can route a packet based data
message to the service provider NPL component 161 (or other
component of the service provider computing device). This packet
based data message can cause the service provider computing device
160 to effect a conversion, e.g., to make a car pick up reservation
outside the movie theater. This conversion--or confirmed order--(or
any other conversion of any other action of the thread) can occur
prior to completion of one or more actions of the thread, such as
prior to completion of the movie, as well as subsequent to
completion of one or more actions of the thread, such as subsequent
to dinner.
[0071] Based on a response to a content item for a subsequent
action in the thread, such as the response "yes please" to the
content item "would you like a ride home from the movie theater"
for the third and last action in a sequence dependent thread, the
data processing system 105 can initiate a conversion or action.
This can occur before the end user has begun any activities
associated with the thread, e.g., before dinner or before the movie
is over. Processors of the data processing system 105 can invoke
the direct action API 135 to execute scripts that order a car from
a car share service. The direct action API 135 can obtain content
data 148 (or parameters 146 or policies 147) from the data
repository 145, as well as data received with end user consent from
the client computing device 150 to determine location, time, user
accounts, logistical or other information in order to reserve a car
from the car share service. Using the direct action API 135, the
data processing system 105 can also communicate with the service
provider computing device 160 to complete the conversion by in this
example making the car share pick up reservation.
[0072] The direct action API 135 can initiate the conversion or
activity to accomplish an action of the thread at any time during a
time period from receipt by the data processing system 105 of the
first input audio signal associated with the thread, (e.g., "OK, I
would like to go to go dinner and then a movie tonight") until a
threshold time period subsequent to completion of one of the
actions of the thread, (e.g., until 15 minutes after the end of the
second action of watching the movie). The data processing system
110 can also determine the end of this time period based on other
factors, such as an indication that the end user has completed the
actions of the thread, e.g., has returned home or is no longer
located at the movie theater. The data processing system 105 can
also obtain an indication from the client computing device 150 (a
data message transmitted via the network 165) that the thread is
cancelled or dormant or that the end user has cancelled or
completed actions of the thread.
[0073] The direct action API 135 can initiate the conversion or
activity to accomplish an action of the thread based on completion
or time of completion of other actions of the thread. For example,
the data processing system 105 can order a good or service (car
share pick-up) directly or by communicating with the service
provider computing device 160 within a threshold time period of a
conclusion of a prior action in the thread. Within 5 minutes (or
other time period) prior or subsequent to the scheduled or actual
conclusion of the movie (second action), the data processing system
105 can confirm or order a car share service to send a car to pick
up the end user at the movie theater (subsequent, third action).
This can occur in the absence of input received from the end user
computing device 150 during this time period, or responsive to a
prompt received from the end user computing device 150 during this
time period.
[0074] The direct action API 135 can initiate the conversions or
other activity associated with the sequence dependent operations of
the thread in any order. For example, the direct action API 135 (or
other data processing system 105 component) can initiate activity
corresponding to a final action (e.g., the third action in a three
action thread such as ordering a taxi) prior to initiating activity
corresponding to an earlier thread in the sequence, (e.g., prior to
making a dinner reservation or prior to ordering movie tickets). In
this example the data processing system 105 initiates activity for
an earlier (e.g., second) action subsequent to initiation of
activity for the later (e.g., third) action.
[0075] The content selector component 125 can identify, select, or
obtain multiple content items resulting from a multiple content
selection processes. The content selection processes can be
real-time, e.g., part of the same conversation, communication
session, or series of communications sessions between the data
processing system 105 and the client computing device 150 that
involve a thread. The conversation can include asynchronous
communications separated from one another by a period of hours or
days, for example. The conversation or communication session can
last for a time period from receipt of the first input audio signal
until an estimated or known conclusion of a final action of the
thread, receipt by the data processing system 105 of an indication
of a termination of the thread. This can be referred to as the
active time period of the thread. For example, for a thread with
three actions (e.g., dinner, move, and transport home), the content
selector component 125 can select at least one content item for
each action. The content item selector component 125 can run or
obtain results from a different content selection process for each
action. In the content selection processes the content provider
computing device 150 can set forth content items for selection by
the content selector component 125. For a thread with at least
three actions, the content item selector component can select or
otherwise identify a first content item for the first action via a
first content selection process, a second content item for the
second action via a second content selection process, and a third
content item for the third action via a third content selection
process. The data processing system 105 that provides these content
items for rendering by the client computing device 150 during the
active time period of the thread can be considered to be operating
in real-time. In this example the content selection processes and
rendering of the content items occurs in real time.
[0076] The data processing system 105 can cancel actions associated
with content items. For example, after ordering the car service the
end user may watch the movie but then decide to walk home, or to
have desert after the movie instead of taking a car home. An app or
other program executing at the client computing device 150 as part
of the data processing system 105 can receive an input audio signal
of "cancel my ride home". The NLP component 110 can receive this
input audio signal, for example as one or more packet based data
messages, and can determine that this input audio signal relates to
a pre-existing thread (e.g., dinner, movie, transport home) and is
part of the same conversation or communication. For example, the
NLP component 110 (or other data processing system 105 component)
can evaluate time data, location data and pre-existing thread data
such as past, present, or scheduled actions of a thread from the
content data 148 of the data repository 145 to determine that an
input audio signal relates to a pre-existing thread. Based, for
example, on the request "ride" or the trigger keyword "cancel" the
NLP component 110 can determine that the input audio signal "cancel
my ride home" relates to the content item "would you like a ride
home from the movie theater?" that corresponds to the third action
of a pre-existing thread. The direct action API 135 (or other
component) can cause the data processing system 105 to communicate
via the interface 115 with the service provider computing device
160 to cancel the order for the taxi or car share service to have a
car waiting for the end user outside the movie theater upon
conclusion of the movie.
[0077] The NLP component 135 can receive the data packet or other
protocol based message to cancel an action of the thread prior to
or subsequent to completion of any action of the thread. The NLP
component 135 can receive from the client computing device 150 (or
obtain from the data repository 145) a data message (inbound audio
signal) to cancel an action of the thread within a time interval
triggered by an earlier action of the thread. For example, in a
sequence dependent thread with three actions, dinner, movie,
transport, the data processing system 105 can receive the transport
cancellation data message within 5 minutes (or other time period)
of the conclusion of the movie. The data processing system 105 can
prompt for confirmation of a product or service related to an
action of the thread. For example, during a time period between the
first action and the second action (e.g., after dinner and before
the movie) the data processing system 105 can transmit a data
message to the client computing device 150 that, when rendered at
the client computing device 150 outputs the audio or text message
stating "just confirming that you still want a car waiting for you
after the movie." The data processing system 105 can receive a
response, e.g., "yes, confirmed" or "no, cancel the car". This
response can be included as part of the thread. The direct action
API 135 can execute scripts to process this information and can
communicate with the service provider computing device 160 to
indicate the confirmation or the cancellation.
[0078] Referring to FIG. 1 and FIG. 2, among others, based on the
sequence dependency parameter, the thread optimization component
120 can create at least one single thread data structure 200. The
single thread data structure 200 can include a packet based
architecture (or other format) and can include at least one header
205. The header 205 can include supplemental data identifying the
data processing system 105, source or destination address
information, governing protocol information, IP addresses, frame
synchronization data, size data, resolution data, or metadata
associated with action data structures. The payload or body of the
single thread data structure 200 can include at least one sequence
dependency parameter 210, or other information such as at least one
first data transmission 215 or at least one second data
transmission 220. The single thread data structure 200 can include
one or more than one structures, e.g., multiple packets having
respective headers 205 and payloads indicating at least part of the
first data transmission 215 or the second data transmission 220.
The sequence dependency parameter 215 can indicate a sequence
dependency of actions from the plurality of actions indicated by
the first data transmission 215 or the second data transmission
220.
[0079] The header 205, sequence dependency parameter 210, first
data transmission 215, and the second data transmission 220 may but
need not be included in the single thread data structure 200. For
example, the body of the single thread data structure 200 can
include only the first data transmission 215 (or portion thereof)
and not include any of the sequence dependency parameter 210 or the
second data transmission 220, or the body of the single thread data
structure 200 can include the sequence dependency parameter 210 as
well as one or more of the first data transmission 215 and the
second data transmission 220. The single thread data structure 200
can include one or more individual packets transmitted separately
in sequence or parallel as part of one or more data transmissions
between the data processing system 105 and the service provider
computing device 160 or the content provider computing device 155.
The header 205 or the sequence dependency parameter 210 can
indicate that the separate transmissions or separate data packets
are associated with the same batch transmission, e.g., the same
overall single thread data structure 200. The direct action API 135
can merge or otherwise link together multiple different single
thread data structures into one single thread data structure 200.
The single thread data structure 200 can include multiple packets
or multiple different structures that are separate but associated
with one another.
[0080] The thread optimization component 120 can prioritize one
action of the single thread data structure 200 over another action.
The prioritization can be indicated by the sequence dependency
parameter 210 or otherwise provided to the direct action API 135 or
the content selector component 125. For example, the thread
optimization component 120 can prioritize a first in time action
indicated by the single thread data structure 200. Responsive to
the prioritization, the direct action API 135 or other component
such as the content selector component 125 can provide data
transmissions (e.g., at least part of the first data transmission
215 or the second data transmission 220) to the content provider
computing device 155 or to the service provider computing device
160 to effect a conversion related to the first in time action.
[0081] Referring to FIG. 3, among others, the data processing
system 105 can receive, from a first client computing device 150,
the first input audio signal 305, (e.g., "OK, I would like to go to
go dinner tonight"). The data processing system 105 can also
receive, from the same or a different client computing device 150,
the second input audio signal 310, (e.g., "OK, I would like to
catch a movie later"). The data processing system 105 can generate
respective action data structures and corresponding data
transmissions for the first and second audio input signals 305,
310. Data processing system 105 components such as the thread
optimization component 120 can apply statistical or heuristic
techniques to the first input audio signal 305 and the second input
audio signal 310 to generate at least one sequence dependency
parameter indicative of sequence dependent actions from among the
actions of the first input audio signal 305 and the second input
audio signal 310. The data processing system 105 can batch or pool
the data transmission (e.g., packets) or the action data structures
corresponding to the first input audio signal 305 and the second
input audio signal 310 to create the batched or pooled single
thread data structure 200. The data processing system 105 can
transmit or otherwise provide the single thread data structure 200
to the service provider computing device 160 for processing by the
service provider computing device 160 to, for example reserve at
least one car, purchase movie tickets, or make a dinner reservation
responsive to the first and second input audio signals 305,
310.
[0082] Different instances of portions of the same single thread
data structure can be provided to different computing devices. For
example, all or some of the single thread 200 can be provided to a
service provider computing device 160 to effect a conversion, e.g.,
order a car from a car share service, and the same or different
portions of the single thread 200 can be provided (simultaneously
is sequentially) to a content provider computing device 155 to
effect another conversion, e.g., obtain a content item for a
restaurant.
[0083] Responsive to receipt of the single thread data structure
200, the content provider computing device 155 or the service
provider computing device 160 can perform at least one operation
defined or indicated by the single thread data structure 200. The
operation can correspond to one or more of the respective actions
of the action data structures (or data transmissions) of the first
or second input audio signals 305, 310. For example, the operations
can include reserving a car from a car share service, from the
service provider computing device 160, or providing a content item
for a movie. For example, the content provider computing device 155
can provide a first response 315 (e.g., a content item for a movie)
to the client computing device 150, and the service provider
computing device 160 can provide a second response 320 (e.g., to
reserve a car) to the same or a different client computing device
150. The first and second responses 315, 320, can bypass the data
processing system 105 during transmission from the content provider
computing device 155 or the service provider computing device 160
to the client computing device 150. The responses 315, 320, can
include text, image, or other data messages (including audio) that
confirm a conversion action, such as a reservation for a car from a
car service or rending of a content item. The data processing
system 105 can receive an indication of the conversion (or of the
responses 315, 320) via the computer network 165 from the service
provider computing device 160, the content provider computing
device 155, or from the client computing device 150.
[0084] The single thread 200 created by the data processing system
105 (e.g., by the thread optimization component 120 or the direct
action API 135) can indicate an actual, known, scheduled, or
estimated time of actions that correspond to the thread. These
times can include movie start times, transport pick up times,
dinner reservation times, or event times, among others. The times
can be discrete times, e.g., 8:00 pm dinner reservations, or
relative times relative to other actions, e.g., the action `B` is
scheduled to begin 15 minutes after the known or estimated
conclusion time of action `A`. For example, the thread 200 can
indicate that a first action (e.g., eating dinner) is scheduled to
occur prior to a second action (e.g. watching a movie). These
actions can correspond to data structure (or data transmission)
actions identified from input audio signals. The direct action API
135 can detect the completion of a first action. For example, the
computing device 150 can execute a script to pay the bill at the
restaurant, or the direct action API 135 can estimate that dinner
will last for 90 minutes, or the end user can provide an audio
input signal or other data message to indicate that the first
action is complete or scheduled for completion at a time or within
a time window. Responsive to detection of completion (e.g., a known
or estimate end time) of a first action, the direct action API 135
can proceed to transmit data packets of the single thread to a
service provider computing device 160 or to a content provider
computing device 155. This transmission can occur subsequent to
known or estimated completion of the first action, or during a time
window, (e.g., within one hour) of known or estimated completion of
the first action. For example, upon completion of dinner, the
direct action API 135 can provide at least part of the single
thread 200 to a service provider computing device 160 to purchase
movie tickets, or to a content provider computing device 155 to
obtain a content item for a movie. Indications of the conversions
(e.g., purchase of the tickets or rendering of the content item at
the client computing device 150) can be provided to the data
processing system 105 from the client computing device 150, the
content provider computing device 155, or the service provider
computing device 160. The sequence dependency parameter 210 can
indicate the order in which actions of the single thread 200 are
scheduled to occur, e.g., can indicate that a first action is
scheduled to occur prior to a second action.
[0085] The direct action API 135 can identify at least one deadlock
condition of at least one action of the single thread 200. A
deadlock condition can indicate that a second action cannot proceed
until after a first, prior action is complete. For example, the
direct action API 135 can identify a deadlock condition when the
first action is a movie action (watching a movie in a theater) and
a second action is transport home via a car share service after the
movie is over. The direct action API 135 can determine a deadlock
condition for the second action (e.g., the ride home) that lasts
until a time associated with the first action, such as a scheduled
end time of the movie. The direct action API 135 or other component
such as the interface 115 can prevent transmission of the data
transmission to a service provider computing device (e.g., a car
share service) responsive to the deadlock condition. For example,
the data processing system 105 or component thereof can prevent
transmission of data packets of the data transmission (or data
structure) for the action (e.g., to reserve a car) to a service
provider computing device 160 (e.g., of a car share service) during
the time period of the deadlock condition. This prevents the
service provider computing device 160 from receiving the request
for a car (or other service) too early.
[0086] The direct action API 135 can obtain an indication or
otherwise determine that the deadlock condition has terminated or
no longer exists. For example, the direct action API 135 can query
the service provider computing device 160 or other third party
computing device to determine a scheduled end time of a movie or
other action. Upon arrival of this time, or within a threshold time
period (e.g., 30 minutes or 5 minutes) in advance of this time the
direct action API can break, release, or terminate the deadlock
condition. Subsequent to expiration of the deadlock condition the
data processing system 105 can transmit (e.g., via the interface
105) to the service provider computing device 160 data of the data
transmission or data structure corresponding to a subsequent action
such as a ride home after the movie.
[0087] The direct action API 135 can receive an indication form the
client computing device 150 to terminate the deadlock condition.
For example, the end user may decide to leave the movie early,
before the movie is finished, and can enter an input audio signal
into the client computing device, e.g., "OK, this movie stinks, I'd
like a ride home please". The data processing system 105 (e.g., the
NLP component 110 or the direct action API 135) can determine from
this input audio signal that the deadlock condition has expired,
and can transmit data for the subsequent action to the service
provider computing device 160. Subsequent to release of the
deadlock condition the direct action API 135 can also provide data
for an action (e.g., data of a data transmission or action data
structure of the single thread 200) to the content provider
computing device 155 to obtain a content item related to the
post-deadlock action. The content item can be provided by the data
processing system 105 or by the content provider computing device
155 to the client computing device 150 for rendering. The content
item can indicate, for example, "Sorry to hear about the movie,
would you like to order a car from a car share company?". The
content selector component 125 (or other component such as the
interface 115 or the direct action API 135) can block selection of
the content item, or transmission of the selected content item to
the client computing device 150, responsive to a deadlock condition
or until release of the deadlock condition.
[0088] The direct action API 135 can modify sequential orders of
actions indicated by the single thread 200. For example, the direct
action API can determine an indication of a first sequential order,
e.g., a first action, a second action subsequent to the first
action, and a third action subsequent to the second action (dinner,
then a movie, then a ride home). The direct action API 135 and
other components such as the NLP component 110 and the interface
115 can receive a request to modify the sequential order. For
example, the data processing system 105 can receive in input audio
signal from the client computing device of "OK I'd like to eat
dinner after the movie." The direct action API 135 (or NLP
component 110) can obtain from this audio input signal a request to
modify the sequential order of the actions to, for example, a
movie, then dinner, then a ride home. From this information, the
direct action API 135 can generate a modified sequential order so
that the second action (watching the movie) is now scheduled to
occur prior to the first action (eating dinner). The direct action
API 135 or content selector component 125 (or other components) can
proceed accordingly to transmit data transmission of the movie
action prior to data transmissions of the dinner action to the
content provider computing device 155 or the service provider
computing device 160. The direct action API 135 can also identify
or modify a deadlock condition to delay operations related to the
dinner action based on an end time of the first movie action. The
actions of dinner, movies, and transport are examples and any
number of end user activities or requests can constitute actions.
The modifications can occur responsive to inputs other than the
input audio signal. For example, if tickets to the 9 pm movie
(after dinner) are sold out, the data processing system 105 can
provide an audio output for rendering at the client computing
device 150 to suggest watching a movie (e.g., the 5 pm showing)
prior to dinner.
[0089] The data processing system 105 can perform offline action.
This can save processing and electrical power requirements and
reduce or shift network traffic to off-peak times. For example, the
single thread 200 can indicate a first action and a second
subsequent action that depends on resolution of the first action.
These actions can be days or weeks (or more) apart from one
another, such as buying a plane ticket (first action, today) for a
three week tropical beach vacation that will occur six months in
the future, and booking scuba lessons for the last day of the
vacation (second action, more than six months away). The direct
action API 135 can communicate in real time with the service
provider computing device 160 corresponding to an airline entity
responsive to receipt of the input audio signal to buy the plane
tickets in an online action to effect a conversion--the purchase of
the plane tickets. The second action in this example remains six
months away. Over this six month period or other time window the
direct action API 135 or other component such as the content
selector component 125 can select content items or perform other
operations responsive to the second action (scuba lessons). For
example, the direct action API can obtain offline by obtaining this
information from the data repository 145 or from a third party data
repository relating to scuba lessons. The offline action may or may
not be in real time, and an offline action does not require time
separation (e.g., six months) between actions. For example, the
data processing system 105 can obtain information responsive to
actions from the data repository 145 or from a third party database
in a real time, as part of a communication session or synchronous
or asynchronous conversation with the client computing device.
[0090] FIG. 4 depicts a method 400 to manage voice activated audio
input data communications that indicate sequence dependent
operations in a voice activated data packet based computer network
environment. The method 400 can receive at least one first audio
input signal (ACT 405). For example, via the interface 115 the NLP
component can receive data packets (ACT 405). The data processing
system 105 can execute, launch, or invoke the NLP component 110 to
receive packet or other protocol based transmissions via the
network from at least one client computing device 150. The data
packets can include or correspond to an input audio signal detected
by the sensor 151 of a first client computing device 150, such as a
first end user saying "OK, I would like to go to go dinner tonight"
into the client computing device 150, e.g., a smartphone. The
method 400 can parse the input audio signal to identify at least
one first request or at least one first trigger keyword from the
input audio signal (ACT 410). For example, the NLP component 110
can parse the input audio signal to identify requests (an
entertainment request for "dinner") as well as trigger keywords
("to go to") that correspond or relate to the request. The method
400 can generate at least one first action data structure (ACT 415)
based on the identified requests or keywords associated with the
received first audio input signal. For example, the direct action
API 135 can generate an action data structure that indicates a
first action, such as a location for a taxi pick-up, a requested
service provider, or a restaurant recommendation.
[0091] The method 400 can receive at least one second audio input
signal (ACT 420). For example, the NLP component 110 can receive
packet or other protocol based transmissions via the network 165
from the same or a different client computing device 150 that
originated the first input audio signal. The data packets can
include or correspond to an input audio signal detected by the
sensor 151 of the second client computing device 150, such as an
end user saying "OK, I would like to catch a movie later" into the
client computing device 150. The method 400 can identify at least
one second request or at least one second trigger keyword from the
second input audio signal (ACT 425). For example, the NLP component
110 can parse the input audio signal to identify requests (an
entertainment request for a "movie") as well as trigger keywords
("to catch") that correspond or relate to the request. The method
400 can generate at least one second action data structure (ACT
430) based on the identified requests or keywords associated with
the received first audio input signal. For example, the direct
action API 135 can generate an action data structure that indicates
a second action, such as a location for a taxi pick-up, a requested
service provider, or movie information.
[0092] The method 400 can construct data transmissions from the
action data structures (ACT 435). For example, the direct action
API 135 can create a first data transmission from the first action
data structure that corresponds to the first input audio signal,
and can create a second data transmission from the second action
data structure that corresponds to the second input audio signal.
The first and second (or other number of) data transmissions can be
constructed or generated (ACT 435) by packetizing information
obtained from the corresponding action data structures, or
otherwise converting the action data structures into a form for
transmission as part of a broadly defined communication session,
e.g., a back and forth or asynchronous conversation or transmission
of data between the end user computing device 150 and the content
provider computing device 155 or the service provider computing
device 160 via the data processing system 105. Communication
sessions with multiple third party devices (e.g., content provider
computing devices 155 or service provider computing devices 160)
that correspond to different entities can be considered part of a
common communication session. Communication sessions can be
synchronous, with back and forth data transmission to and from the
client computing device 150 in a conversational matter, or
asynchronous where a period of dormancy, e.g., at least one hour,
exists between data transmissions.
[0093] The method 400 can obtain data from the data transmissions
(ACT 440). For example, the thread optimization component 120 can
access or retrieve (e.g., from the data repository 145) information
regarding actions from the data transmissions (or from the
corresponding action data structures). The method 400 can determine
at least one sequence dependency parameter (ACT 445). For example,
based on data obtained from the data transmissions (ACT 440) that
indicate an order of operations or sequence dependency of actions,
the thread optimization component 120 can determine a sequence
dependency parameter that indicates the existence of a sequence
dependency for at least two actions. The method 400 can associate
one or more action data structures (directly or via association of
corresponding data transmissions) with the single thread data
structure 200. For example, the thread optimization component 120
(or other data processing system 105 component) can generate the
single thread data structure 200 (ACT 450). For example, based on
the indication of at least two sequence or time dependent
operations, the thread optimization component 120 can generate at
least one single thread data structure that indicates the first and
second data transmissions, first and second action data structures,
or their associated actions (ACT 440). The generated single thread
data structure 200 (ACT 450) can include data used by the direct
action API 135 to detect completion of an action, so that to the
data processing system 105 can then provide data packets for a
different action to the service provider computing device 160 or to
the content provider computing device 155. The data processing
system 105 can also identify a deadlock condition associated with
actions of the generated single thread data structure 200 (ACT
450). The single thread data structure 200 can indicate a
sequential order of multiple actions, and the method can generate a
modified sequential order that changes the sequential order of the
actions. The data processing system 105 can provide all or part of
the single thread data structure 200 to one or more content
provider computing devices 155 or service provider computing
devices 160.
[0094] FIG. 5 is a block diagram of an example computer system 500.
The computer system or computing device 500 can include or be used
to implement the system 100, or its components such as the data
processing system 105. The computing system 500 includes a bus 505
or other communication component for communicating information and
a processor 510 or processing circuit coupled to the bus 505 for
processing information. The computing system 500 can also include
one or more processors 510 or processing circuits coupled to the
bus for processing information. The computing system 500 also
includes main memory 515, such as a random access memory (RAM) or
other dynamic storage device, coupled to the bus 505 for storing
information, and instructions to be executed by the processor 510.
The main memory 515 can be or include the data repository 145. The
main memory 515 can also be used for storing position information,
temporary variables, or other intermediate information during
execution of instructions by the processor 510. The computing
system 500 may further include a read only memory (ROM) 520 or
other static storage device coupled to the bus 505 for storing
static information and instructions for the processor 510. A
storage device 525, such as a solid state device, magnetic disk or
optical disk, can be coupled to the bus 505 to persistently store
information and instructions. The storage device 525 can include or
be part of the data repository 145.
[0095] The computing system 500 may be coupled via the bus 505 to a
display 535, such as a liquid crystal display, or active matrix
display, for displaying information to a user. An input device 530,
such as a keyboard including alphanumeric and other keys, may be
coupled to the bus 505 for communicating information and command
selections to the processor 510. The input device 530 can include a
touch screen display 535. The input device 530 can also include a
cursor control, such as a mouse, a trackball, or cursor direction
keys, for communicating direction information and command
selections to the processor 510 and for controlling cursor movement
on the display 535. The display 535 can be part of the data
processing system 105, the client computing device 150 or other
component of FIG. 1, for example.
[0096] The processes, systems and methods described herein can be
implemented by the computing system 500 in response to the
processor 510 executing an arrangement of instructions contained in
main memory 515. Such instructions can be read into main memory 515
from another computer-readable medium, such as the storage device
525. Execution of the arrangement of instructions contained in main
memory 515 causes the computing system 500 to perform the
illustrative processes described herein. One or more processors in
a multi-processing arrangement may also be employed to execute the
instructions contained in main memory 515. Hard-wired circuitry can
be used in place of or in combination with software instructions
together with the systems and methods described herein. Systems and
methods described herein are not limited to any specific
combination of hardware circuitry and software.
[0097] Although an example computing system has been described in
FIG. 5, the subject matter including the operations described in
this specification can be implemented in other types of digital
electronic circuitry, or in computer software, firmware, or
hardware, including the structures disclosed in this specification
and their structural equivalents, or in combinations of one or more
of them.
[0098] For situations in which the systems discussed herein collect
personal information about users, or may make use of personal
information, the users may be provided with an opportunity to
control whether programs or features that may collect personal
information (e.g., information about a user's social network,
social actions or activities, a user's preferences, or a user's
location), or to control whether or how to receive content from a
content server or other data processing system that may be more
relevant to the user. In addition, certain data may be anonymized
in one or more ways before it is stored or used, so that personally
identifiable information is removed when generating parameters. For
example, a user's identity may be anonymized so that no personally
identifiable information can be determined for the user, or a
user's geographic location may be generalized where location
information is obtained (such as to a city, postal code, or state
level), so that a particular location of a user cannot be
determined. Thus, the user may have control over how information is
collected about him or her and used by the content server.
[0099] The subject matter and the operations described in this
specification can be implemented in digital electronic circuitry,
or in computer software, firmware, or hardware, including the
structures disclosed in this specification and their structural
equivalents, or in combinations of one or more of them. The subject
matter described in this specification can be implemented as one or
more computer programs, e.g., one or more circuits of computer
program instructions, encoded on one or more computer storage media
for execution by, or to control the operation of, data processing
apparatuses. Alternatively or in addition, the program instructions
can be encoded on an artificially generated propagated signal,
e.g., a machine-generated electrical, optical, or electromagnetic
signal that is generated to encode information for transmission to
suitable receiver apparatus for execution by a data processing
apparatus. A computer storage medium can be, or be included in, a
computer-readable storage device, a computer-readable storage
substrate, a random or serial access memory array or device, or a
combination of one or more of them. While a computer storage medium
is not a propagated signal, a computer storage medium can be a
source or destination of computer program instructions encoded in
an artificially generated propagated signal. The computer storage
medium can also be, or be included in, one or more separate
components or media (e.g., multiple CDs, disks, or other storage
devices). The operations described in this specification can be
implemented as operations performed by a data processing apparatus
on data stored on one or more computer-readable storage devices or
received from other sources.
[0100] The terms "data processing system" "computing device"
"component" or "data processing apparatus" encompass various
apparatuses, devices, and machines for processing data, including
by way of example a programmable processor, a computer, a system on
a chip, or multiple ones, or combinations of the foregoing. The
apparatus can include special purpose logic circuitry, e.g., an
FPGA (field programmable gate array) or an ASIC (application
specific integrated circuit). The apparatus can also include, in
addition to hardware, code that creates an execution environment
for the computer program in question, e.g., code that constitutes
processor firmware, a protocol stack, a database management system,
an operating system, a cross-platform runtime environment, a
virtual machine, or a combination of one or more of them. The
apparatus and execution environment can realize various different
computing model infrastructures, such as web services, distributed
computing and grid computing infrastructures. The direct action API
135, content selector component 125, thread optimization component
120 or NLP component 110 and other data processing system 105
components can include or share one or more data processing
apparatuses, systems, computing devices, or processors.
[0101] A computer program (also known as a program, software,
software application, app, script, or code) can be written in any
form of programming language, including compiled or interpreted
languages, declarative or procedural languages, and can be deployed
in any form, including as a stand-alone program or as a module,
component, subroutine, object, or other unit suitable for use in a
computing environment. A computer program can correspond to a file
in a file system. A computer program can be stored in a portion of
a file that holds other programs or data (e.g., one or more scripts
stored in a markup language document), in a single file dedicated
to the program in question, or in multiple coordinated files (e.g.,
files that store one or more modules, sub-programs, or portions of
code). A computer program can be deployed to be executed on one
computer or on multiple computers that are located at one site or
distributed across multiple sites and interconnected by a
communication network.
[0102] The processes and logic flows described in this
specification can be performed by one or more programmable
processors executing one or more computer programs (e.g.,
components of the data processing system 105) to perform actions by
operating on input data and generating output. The processes and
logic flows can also be performed by, and apparatuses can also be
implemented as, special purpose logic circuitry, e.g., an FPGA
(field programmable gate array) or an ASIC (application-specific
integrated circuit). Devices suitable for storing computer program
instructions and data include all forms of non-volatile memory,
media and memory devices, including by way of example semiconductor
memory devices, e.g., EPROM, EEPROM, and flash memory devices;
magnetic disks, e.g., internal hard disks or removable disks;
magneto optical disks; and CD ROM and DVD-ROM disks. The processor
and the memory can be supplemented by, or incorporated in, special
purpose logic circuitry.
[0103] The subject matter described herein can be implemented in a
computing system that includes a back-end component, e.g., as a
data server, or that includes a middleware component, e.g., an
application server, or that includes a front-end component, e.g., a
client computer having a graphical user interface or a web browser
through which a user can interact with an implementation of the
subject matter described in this specification, or a combination of
one or more such back-end, middleware, or front-end components. The
components of the system can be interconnected by any form or
medium of digital data communication, e.g., a communication
network. Examples of communication networks include a local area
network ("LAN") and a wide area network ("WAN"), an inter-network
(e.g., the Internet), and peer-to-peer networks (e.g., ad hoc
peer-to-peer networks).
[0104] The computing system such as system 100 or system 500 can
include clients and servers. A client and server are generally
remote from each other and typically interact through a
communication network (e.g., the network 165). The relationship of
client and server arises by virtue of computer programs running on
the respective computers and having a client-server relationship to
each other. In some implementations, a server transmits data (e.g.,
data packets representing a content item) to a client computing
device (e.g., for purposes of displaying data to and receiving user
input from a user interacting with the client computing device).
Data generated at the client computing device (e.g., a result of
the user interaction) can be received from the client computing
device at the server (e.g., received by the data processing system
105 from the computing device 150 or the content provider computing
device 155 or the service provider computing device 160).
[0105] While operations are depicted in the drawings in a
particular order, such operations are not required to be performed
in the particular order shown or in sequential order, and all
illustrated operations are not required to be performed. Actions
described herein can be performed in a different order.
[0106] The separation of various system components does not require
separation in all implementations, and the described program
components can be included in a single hardware or software
product. For example, the NLP component 110, the content selector
component 125, or the thread optimization component 120 can be a
single component, app, or program, or a logic device having one or
more processing circuits, or part of one or more servers of the
data processing system 105.
[0107] Having now described some illustrative implementations, it
is apparent that the foregoing is illustrative and not limiting,
having been presented by way of example. In particular, although
many of the examples presented herein involve specific combinations
of method acts or system elements, those acts and those elements
may be combined in other ways to accomplish the same objectives.
Acts, elements and features discussed in connection with one
implementation are not intended to be excluded from a similar role
in other implementations or implementations.
[0108] The phraseology and terminology used herein is for the
purpose of description and should not be regarded as limiting. The
use of "including" "comprising" "having" "containing" "involving"
"characterized by" "characterized in that" and variations thereof
herein, is meant to encompass the items listed thereafter,
equivalents thereof, and additional items, as well as alternate
implementations consisting of the items listed thereafter
exclusively. In one implementation, the systems and methods
described herein consist of one, each combination of more than one,
or all of the described elements, acts, or components.
[0109] Any references to implementations or elements or acts of the
systems and methods herein referred to in the singular may also
embrace implementations including a plurality of these elements,
and any references in plural to any implementation or element or
act herein may also embrace implementations including only a single
element. References in the singular or plural form are not intended
to limit the presently disclosed systems or methods, their
components, acts, or elements to single or plural configurations.
References to any act or element being based on any information,
act or element may include implementations where the act or element
is based at least in part on any information, act, or element.
[0110] Any implementation disclosed herein may be combined with any
other implementation or embodiment, and references to "an
implementation," "some implementations," "one implementation" or
the like are not necessarily mutually exclusive and are intended to
indicate that a particular feature, structure, or characteristic
described in connection with the implementation may be included in
at least one implementation or embodiment. Such terms as used
herein are not necessarily all referring to the same
implementation. Any implementation may be combined with any other
implementation, inclusively or exclusively, in any manner
consistent with the aspects and implementations disclosed
herein.
[0111] References to "or" may be construed as inclusive so that any
terms described using "or" may indicate any of a single, more than
one, and all of the described terms. For example, a reference to
"at least one of `A` and `B`" can include only `A`, only `B`, as
well as both `A` and `B`. Such references used in conjunction with
"comprising" or other open terminology can include additional
items.
[0112] Where technical features in the drawings, detailed
description or any claim are followed by reference signs, the
reference signs have been included to increase the intelligibility
of the drawings, detailed description, and claims. Accordingly,
neither the reference signs nor their absence have any limiting
effect on the scope of any claim elements.
[0113] The systems and methods described herein may be embodied in
other specific forms without departing from the characteristics
thereof. For example, components of the data processing system 105
need not be separate components, and one component can include
other components. Processors of one or more computing devices
(e.g., servers) can include or execute components of the data
processing system 105. The foregoing implementations are
illustrative rather than limiting of the described systems and
methods. Scope of the systems and methods described herein is thus
indicated by the appended claims, rather than the foregoing
description, and changes that come within the meaning and range of
equivalency of the claims are embraced therein.
* * * * *