U.S. patent application number 15/917472 was filed with the patent office on 2018-07-12 for time heuristic audio control.
This patent application is currently assigned to Dolby Laboratories Licensing Corporation. The applicant listed for this patent is Dolby Laboratories Licensing Corporation. Invention is credited to Jeffrey Baker, Matthew J. Jaffe, Noah Kraft, Richard Fritz Lanman, III.
Application Number | 20180199130 15/917472 |
Document ID | / |
Family ID | 55349458 |
Filed Date | 2018-07-12 |
United States Patent
Application |
20180199130 |
Kind Code |
A1 |
Jaffe; Matthew J. ; et
al. |
July 12, 2018 |
Time Heuristic Audio Control
Abstract
A time heuristic audio control system, comprises a receiver for
receiving time-based data from a personal computing device and a
memory storing one or more sets processing parameters comprising
instructions for processing the ambient sound based upon the
time-based data. The system further includes a processor coupled to
the memory and the receiver configured to adjust the ambient sound
as directed by a selected set of processing parameters retrieved
from the memory to create adjusted audio, the selected set of
processing parameters retrieved based upon the time-based data and
at least one speaker for outputting the adjusted audio.
Inventors: |
Jaffe; Matthew J.; (San
Francisco, CA) ; Kraft; Noah; (Brooklyn, NY) ;
Lanman, III; Richard Fritz; (San Francisco, CA) ;
Baker; Jeffrey; (Newbury Park, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Dolby Laboratories Licensing Corporation |
San Francisco |
CA |
US |
|
|
Assignee: |
Dolby Laboratories Licensing
Corporation
San Francisco
CA
|
Family ID: |
55349458 |
Appl. No.: |
15/917472 |
Filed: |
March 9, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15382475 |
Dec 16, 2016 |
9918159 |
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15917472 |
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14928996 |
Oct 30, 2015 |
9560437 |
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15382475 |
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14681843 |
Apr 8, 2015 |
9524731 |
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14928996 |
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61976794 |
Apr 8, 2014 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04R 2460/07 20130101;
G10L 21/0208 20130101; H04R 1/1083 20130101; H04W 4/80 20180201;
H04R 1/1016 20130101; H04R 27/00 20130101; H04R 2420/07 20130101;
H04R 2227/003 20130101 |
International
Class: |
H04R 1/10 20060101
H04R001/10; G10L 21/0208 20130101 G10L021/0208 |
Claims
1. A time heuristic audio system, comprising: an audio processing
system configured to receive ambient sound and to convert the
ambient sound into a digitized ambient sound signal; a memory
storing one or more sets of processing parameters comprising
instructions for processing the digitized ambient sound signal
based upon time-based data, wherein the time-based data at least
indicates an event or activity; and a processor coupled to the
memory, the processor configured to: receive manually altered
processing parameters and store the time-based data and the
manually altered processing parameters together in the memory; in
the event a user of the time heuristic audio system manually alters
the processing parameters to be a same manually altered processing
parameters more than a threshold numbers of times, update the
memory to use the same manually altered processing parameters when
the event or activity occurs; compare current time data to the
time-based data; and adjust the digitized ambient sound signal to
create an adjusted digitized sound signal based on the same
manually altered processing parameters and when the current time
data matches the time-based data, wherein the audio processing
system is configured to convert the adjusted digitized sound signal
into adjusted ambient sound for output.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This patent is a continuation U.S. patent application Ser.
No. 15/382,475 filed Dec. 16, 2016, which is a continuation of U.S.
patent application Ser. No. 14/928,996 filed Oct. 30, 2015, now
U.S. Pat. No. 9,560,437 issued Jan. 31, 2017, which is a
continuation-in-part of U.S. patent application Ser. No. 14/681,843
filed Apr. 8, 2015, now U.S. Pat. No. 9,524,731 issued Dec. 20,
2016, which claims the benefit of priority to U.S. Provisional
Patent Application No. 61/976,794 filed Apr. 8, 2014, all of which
are incorporated herein by reference in their entirety.
NOTICE OF COPYRIGHTS AND TRADE DRESS
[0002] A portion of the disclosure of this patent document contains
material which is subject to copyright protection. This patent
document may show and/or describe matter which is or may become
trade dress of the owner. The copyright and trade dress owner has
no objection to the facsimile reproduction by anyone of the patent
disclosure as it appears in the Patent and Trademark Office patent
files or records, but otherwise reserves all copyright and trade
dress rights whatsoever.
BACKGROUND
Field
[0003] This disclosure relates generally to a system for time
heuristic audio control. In particular, this disclosure relates to
the adjustment of ambient and secondary audio sources using
time-based data.
Description of the Related Art
[0004] Audio equalization systems have existed for some time.
Through these systems, users of personal audio devices such as
Sony.RTM. Walkman.RTM. or the Apple.RTM. iPod.RTM. have been able
to adjust the relative volume of frequencies in pre-recorded audio
as desired. Similarly, these devices have often employed pre-set
memories that enable users to store preferred equalization settings
or manufacturer-set pre-set settings that may have names, such as
"bass boost" or "symphony" or "super-treble" dependent upon their
particular parameters. Whatever the case, users have been required
to either set the settings and/or store them for later use, or to
select from a group of previously-stored settings as desired.
[0005] In a related field, active and passive noise cancellation to
remove undesirable traits of ambient audio and personal
pre-recorded audio have existed for some time. For example,
Bose.RTM. noise cancelling headphones are known for removing
virtually all ambient sound within desired frequency range from an
environment (e.g. airplane noise while an individual is flying in
an airplane). Simultaneously, these types of systems may include
the capability to output audio, such as pre-recorded audio, through
one or more speakers. However, these systems typically are
all-or-nothing systems in which all external sound is effectively
cancelled or attenuated and any pre-recorded audio is output as-is.
Thus, the noise-cancelling properties are typically "enabled" or
"not enabled."
DESCRIPTION OF THE DRAWINGS
[0006] FIG. 1 is a block diagram of an environment.
[0007] FIG. 2 is block diagram of an audio processing system.
[0008] FIG. 3 is a block diagram of a personal computing
device.
[0009] FIG. 4 is a functional block diagram of a portion of a time
heuristic audio system.
[0010] FIG. 5 is a functional block diagram of a time heuristic
audio system.
[0011] FIG. 6 is a flow chart of a method for creating a time
heuristic audio control.
[0012] FIG. 7 is a flow chart of a method for altering audio
processing parameters in response to a time heuristic audio
control.
[0013] Throughout this description, elements appearing in figures
are assigned three-digit reference designators, where the most
significant digit is the figure number where the element is
introduced and the two least significant digits are specific to the
element. An element not described in conjunction with a figure has
the same characteristics and function as a previously-described
element having the same reference designator.
DETAILED DESCRIPTION
[0014] An individual may wish to pre-define, either through overt
action, or preferably, through machine-learning principles, a set
of audio processing parameters that are to be used when the
individual is known to be at a particular event, location, or
environment. For example, when attending a series of concerts at a
particular venue, a user may repeatedly select one predetermined
set of audio processing parameters. These parameters may, for
example, adjust equalization settings, introduce a reverb and
perform active noise cancellation on aspects of sound while not
eliminating others (e.g. eliminating human voices while not
eliminating any other ambient sound). After a user has selected
those same settings several times when in the particular venue,
those settings may be stored as an automatically-selected set of
processing parameters when calendar data in the individual's
personal computing device (e.g. an iPhone.RTM.) indicates that the
user is at that same concert venue. On the next visit to that
location, based upon time-based data like calendar data, the same
set of processing parameters may be selected automatically.
[0015] As used herein, the phrases "ambient sound" or "ambient
audio" mean sound in the physical location where a user of the time
heuristic audio control system is present. Ambient sound is further
audio that may be heard, either by the user's ears in that physical
location or while in that physical location with the aid of
audio-enhancing technologies. Ambient sound is distinguished from
"secondary audio" or "secondary sound" in that secondary sound and
secondary audio as used herein means audio that is not audible in
the physical location where the user of the combined ambient and
secondary audio system is present either by humans or by the aid of
audio-enhancing technologies. Secondary audio can come from many
different types of sources, but it is distinctly not in the present
physical environment audible to a user of the system. Both ambient
sound and secondary audio may be limited to applications for in-ear
earbuds or over-the-ear headphones that would, without the
reproduction of ambient sound by speakers within the system,
otherwise significantly reduce or virtually eliminate ambient
sound.
[0016] As used herein "time-based data" means data that is
dependent upon or derived from the present, a past, or a future
time. Calendar entries such as appointments, meetings, and
previously-scheduled events are examples of time-based data.
Similarly, "time-based data" may be obtained from other sources
such as text messages, simple message service messages, instant
messaging services, group messaging services, email, and other
text-based communications such that, for example, data indicating a
plan to meet at a particular location at a pre-determined time may
comprise "time-based data."
[0017] Similarly, data attached to any one of these formats may
also be time-based data. For example, an email may include as an
attachment e-tickets or tickets in PDF (portable document format)
form to an event at a concert venue with date and time information
appearing on the face of the tickets. This date and time
information is time-based data. Time-based data may also simply be
the present time as determined by a clock. In situations in which a
user habitually performs an action at a known time every weekday or
every third Tuesday or other similarly-predictable interval, the
present time, noted over the course of multiple occurrences may act
as time-based data. Location data, such as GPS (global positioning
system) data, or assisted GPS data is specifically excluded from
the meaning of "time-based data" as used herein.
[0018] Description of Apparatus
[0019] Referring now to FIG. 1, an environment 100 may include a
cloud 130 and a time heuristic audio system 140. In this context,
the term "cloud" means a network and all devices that may be
accessed by the time heuristic audio system 140 via the network.
The cloud 130 may be a local area network, wide area network, a
virtual network, or some other form of network together with all
devices connected to the network. The cloud 130 may be or include
the Internet. The devices within the cloud 130 may include one or
more servers 132 and one or more personal computing devices
134.
[0020] The time heuristic audio system 140 includes an audio
processing system 110 and a personal computing device 120. While
the personal computing device 120 is shown in FIG. 1 as a smart
phone, the personal computing device 120 may be a smart phone, a
desktop computer, a mobile computer, a wrist-computer, smartwatch,
smartwatch-like device, a tablet computer, or any other computing
device that is capable of performing the processes described
herein. In some cases, some or all of the personal computing device
120 may incorporated within the audio processing system 110 or some
or all of the audio processing system 110 may be incorporated into
the personal computing device.
[0021] The personal computing device 120 may include one or more
processors and memory configured to execute stored software
instructions to perform the processes described herein. For
example, the personal computing device 120 may run an application
program or "app" to perform some or all of the functions described
herein. The personal computing device 120 may include a user
interface comprising a display and at least one input device such
as a touch screen, microphone, keyboard, and/or mouse. The personal
computing device 120 may be configured to perform geo-location,
which is to say to determine its own location and to thereby
generate location data. Geo-location may be performed, for example,
using a Global Positioning System (GPS) receiver or by some other
method.
[0022] The audio processing system 110 may communicate with the
personal computing device 120 via a first wireless communications
link 112. The first wireless communications link 112 may use a
limited-range wireless communications protocol such as
Bluetooth.RTM., Wi-Fi.RTM., ZigBee.RTM., or some other wireless
Personal Area Network (PAN) protocol. The personal computing device
120 may communicate with the cloud 130 via a second communications
link 122. The second communications link 122 may be a wired
connection or may be a wireless communications link using, for
example, the WiFi.RTM. wireless communications protocol, a mobile
telephone data protocol, or another wireless communications
protocol.
[0023] Optionally, the audio processing system 110 may communicate
directly with the cloud 130 via a third wireless communications
link 114. The third wireless communications link 114 may be an
alternative to, or in addition to, the first wireless
communications link 112. The third wireless connection 114 may use,
for example, the WiFi.RTM. wireless communications protocol,
Bluetooth.RTM. or another wireless communications protocol. Still
further, the audio processing system 110 may communicate with the
cloud 130 through the second communications link 122 of the
personal computing device 120 and the first communications link
112.
[0024] FIG. 2 is block diagram of an audio processing system 200.
This may be the audio processing system 110 of FIG. 1. The audio
processing system 200 may include a microphone 210, a preamplifier
215, an analog-to-digital (A/D) converter 220, a wireless interface
225, a processor 230, a memory 235, an analog signal by
digital-to-analog (D/A) converter 240, and amplifier 245, a speaker
250, and a battery (not shown), all of which may be contained
within a housing 290. Some or all of the microphone 210, the
preamplifier 215, the analog-to-digital (A/D) converter 220, the
wireless interface 225, the processor 230, the memory 235, the
analog signal by digital-to-analog (D/A) converter 240, and the
amplifier 245, a speaker 250 elements may be integrated into one or
more integrated microchips or systems-on-chips.
[0025] The housing 290 may be configured to interface with a user's
ear by fitting in, on, or over the user's ear such that ambient
sound is mostly excluded from reaching the user's ear canal and
processed sound generated by the audio processing system 200 is
coupled into the user's ear canal. The housing 290 may have a first
aperture 292 for accepting ambient sound and a second aperture 294
to allow processed sound to be output into the user's outer ear
canal.
[0026] The housing 290 may be, for example, an earbud housing. The
term "earbud" means an apparatus configured to fit, at least
partially, within and be supported by a user's ear. An earbud
housing typically has a portion that fits within or against the
user's outer ear canal. An earbud housing may have other portions
that fit within the concha or pinna of the user's ear.
[0027] The microphone 210 converts received sound 205 (e.g. ambient
sound) into an electrical signal that is amplified by preamplifier
215 and converted into digital sound 222 by A/D converter 220. The
digital sound 222 may be processed by processor 230 to provide
digitized processed sound 232. The processing performed by the
processor 230 will be discussed in more detail subsequently. The
digitized processed sound 232 is converted into an analog signal by
D/A converter 240. The analog signal output from D/A converter 240
is amplified by amplifier 245 and converted into processed output
sound 255 by speaker 250.
[0028] The depiction in FIG. 2 of the audio processing system 200
as a set of functional blocks or elements does not imply any
corresponding physical separation or demarcation. All or portions
of one or more functional elements may be located within a common
circuit device or module. Any of the functional elements may be
divided between two or more circuit devices or modules. For
example, all or portions of the analog-to-digital (A/D) converter
220, the wireless interface 225, the processor 230, the memory 235,
the analog signal by digital-to-analog (D/A) converter 240, and the
amplifier 245 may be contained within a common signal processor
circuit device.
[0029] The microphone 210 may be one or more transducers for
converting sound into an electrical signal that is sufficiently
compact for use within the housing 290.
[0030] The preamplifier 215 may be configured to amplify the
electrical signal output from the microphone 210 to a level
compatible with the input of the A/D converter 220. The
preamplifier 215 may be integrated into the A/D converter 220,
which, in turn, may be integrated with the processor 230. In the
situation where the audio processing system 200 contains more than
one microphone, a separate preamplifier may be provided for each
microphone.
[0031] The A/D converter 220 may digitize the output from
preamplifier 215, which is to say convert the output from
preamplifier 215 into a series of digital ambient sound samples at
a rate at least twice the highest frequency present in the ambient
sound. For example, the A/D converter may output digital sound 222
in the form of sequential sound samples at rate of 40 kHz or
higher. The resolution of the digitized sound 222 (i.e. the number
of bits in each sound sample) may be sufficient to minimize or
avoid audible sampling noise in the processed output sound 255. For
example, the A/D converter 220 may output digitized sound 222
having 12 bits, 14, bits, or even higher resolution. In the
situation where the audio processing system 200 contains more than
one microphone with respective preamplifiers, the outputs from the
preamplifiers may be digitized separately, or the outputs of some
or all of the preamplifiers may be combined prior to
digitization.
[0032] The wireless interface 225 may provide the audio processing
system 200 with a connection to one or more wireless networks 295
using a limited-range wireless communications protocol such as
Bluetooth.RTM., Wi-Fi.RTM., ZigBee.RTM., or other wireless personal
area network protocol. The wireless interface 225 may be used to
receive data such as parameters for use by the processor 230 in
processing the digital ambient sound 222 to produce the digitized
processed sound 232. The wireless interface 225 may be used to
receive digital sound, such as audio from a secondary audio
source.
Alternatively, a hardware interface such as an audio input jack of
various known types (not shown) may enable input of digital
secondary audio to the processor 230. The wireless interface 225
may also be used to export the digitized processed sound 232, which
is to say transmit the digitized processed sound 232 to a device
external to the ambient audio processing system 200. The external
device may then, for example, store and/or publish the digitized
processed sound, for example via social media.
[0033] The processor 230 may include one or more processor devices
such as a microcontroller, a microprocessor, and/or a digital
signal processor. The processor 230 can include and/or be coupled
to the memory 235. The memory 235 may store software programs,
which may include an operating system, for execution by the
processor 230. The memory 235 may also store data for use by the
processor 230. The data stored in the memory 235 may include, for
example, digital sound samples and intermediate results of
processes performed on the digital ambient sound 222. The data
stored in the memory 235 may also include a user's listening
preferences, and/or rules and parameters for applying particular
processes to convert the digital sound 222 into the digitized
processed sound 232 prior to output. The memory 235 may include a
combination of read-only memory, flash memory, and static or
dynamic random access memory.
[0034] The D/A converter 240 may convert the digitized processed
sound 232 from the processor 230 into an analog signal. The
processor 230 may output the digitized processed sound 232 as a
series of samples typically, but not necessarily, at the same rate
as the digital sound 222 is generated by the A/D converter 220. The
analog signal output from the D/A converter 240 may be amplified by
the amplifier 245 and converted into processed output sound 255 by
the speaker 250. The amplifier 245 may be integrated into the D/A
converter 240, which, in turn, may be integrated with the processor
230. The speaker 250 can be any transducer for converting an
electrical signal into sound that is suitably sized for use within
the housing 290.
[0035] The battery (not shown) may provide power to various
elements of the audio processing system 200. The battery may be,
for example, a zinc-air battery, a lithium ion battery, a lithium
polymer battery, a nickel cadmium battery, or a battery using some
other technology.
[0036] FIG. 3 is a block diagram of an exemplary personal computing
device 300 which may be suitable for the personal computing device
120 within the time heuristic audio system 140. As shown in FIG. 3,
the personal computing device 300 includes a processor 310, memory
320, a user interface 330, and a communications interface 340. Some
of these elements may or may not be present, depending on the
implementation. Further, although these elements are shown
independently of one another, each may, in some cases, be
integrated into another.
[0037] The processor 310 may be or include one or more
microprocessors, microcontrollers, digital signal processors,
application specific integrated circuits (ASICs), or a
system-on-a-chip (SOCs). The memory 320 may include a combination
of volatile and/or non-volatile memory including read-only memory
(ROM), static, dynamic, and/or magnetoresistive random access
memory (SRAM, DRM, MRAM, respectively), and nonvolatile writable
memory such as flash memory.
[0038] The communications interface 340 includes at least one
interface for wireless communications with external devices. The
communications interface 340 may include one or more of a cellular
telephone network interface 342, a wireless Local Area Network
(LAN) interface 344, and/or a wireless PAN interface 346. The
cellular telephone network interface 342 may use one or more of the
known 2G, 3G, and 4G cellular data protocols. The wireless LAN
interface 344 may use the WiFi.RTM. wireless communications
protocol or another wireless local area network protocol. The
wireless PAN interface 346 may use a limited-range wireless
communications protocol such as Bluetooth.RTM., Wi-Fi.RTM.,
ZigBee.RTM., or some other wireless personal area network protocol.
When the personal computing device is deployed as part of a time
heuristic audio system, such as the time heuristic audio system
140, the wireless PAN interface 346 may be used to communicate with
one or more audio processing systems 110. The cellular telephone
network interface 342 and/or the wireless LAN interface 344 may be
used to communicate with the cloud 130.
[0039] The communications interface 340 may include radio-frequency
circuits, analog circuits, digital circuits, one or more antennas,
and other hardware, firmware, and software necessary for
communicating with external devices, such as an audio processing
system 110. The communications interface 340 may include one or
more processors to perform functions such as coding/decoding,
compression/decompression, and encryption/decryption as necessary
for communicating with external devices using selected
communications protocols. The communications interface 340 may rely
on the processor 310 to perform some or all of these function in
whole or in part.
[0040] The memory 320 may store software programs and routines for
execution by the processor. These stored software programs may
include an operating system such as the Apple.RTM. iOS or
Android.RTM. operating systems. The operating system may include
functions to support the communications interface 340, such as
protocol stacks, coding/decoding, compression/decompression, and
encryption/decryption. The stored software programs may include an
application or "app" to cause the personal computing device to
perform portions of the processes and functions described
herein.
[0041] The user interface 330 may include a display and one or more
input devices including a touch screen.
[0042] FIG. 4 shows a functional block diagram of a portion of a
time heuristic audio system 400, which may be the system 140. Some
or all of elements of the functional block diagram may be
encompassed within the audio processing system 110 or within the
personal computing device 120. That is to say, the functions and
processing described with reference to FIG. 4 may take place in
whole or in part in one or both of these devices, with the final
sound being delivered to one or more speakers within the audio
processing system 110.
[0043] In the system 400, digitized ambient sound may be received,
for example, from an A/D converter such as the A/D converter 220.
The digitized ambient sound is processed by an audio processing
function 410 implemented by a processor such as the processor 230.
The processor performing the audio processing function may include
one or more processor devices such as a microcontroller, a
microprocessor, and/or a digital signal processor. The audio
processing function 410 may include filtering, equalization,
compression, limiting, and other processes. Filtering may include
high-pass, low-pass, band-pass, and band-reject filtering.
Equalization may include dividing the ambient sound into a
plurality of frequency bands and subjecting each of the bands to a
respective attenuation or gain. Equalization may be combined with
filtering, such as a narrow band-reject filter to suppress a
particular objectionable component of the ambient sound.
Compression may be used to alter the dynamic range of the ambient
sound such that louder sounds are attenuated more than softer
sounds. Compression may be combined with filtering or with
equalization such that louder frequency bands are attenuated more
than softer frequency bands. Limiting may be used to attenuate
louder sounds to a predetermined loudness level without attenuating
softer sounds. Limiting may be combined with filtering or with
equalization such that louder frequency bands are attenuated to a
defined level while softer frequency bands are not attenuated or
attenuated by a smaller amount. Techniques for implementing
filters, compressors, and limiters are known to those of skill in
the art of digital signal processing.
[0044] The audio processing function 410 may also include adding
echo or reverberation to the ambient sound. The audio processing
function 410 may also include detecting and cancelling an echo in
the ambient sound. The audio processing function 410 may further
include noise reduction processing. Techniques to add or suppress
echo, to add reverberation, and to reduce noise are known to those
of skill in the art of digital signal processing. The audio
processing function 410 may include music effects such as chorus,
pitch shifting, flanging, and/or "vinyl" emulation (adding
scratches and pops to emulation vinyl records). Techniques to add
these music effects are known to those of skill in the art of
digital signal processing.
[0045] The audio processing function 410 may be performed in
accordance with processing parameters 425 provided from audio
parameter memory 460 and location based parameter memory 430.
Multiple processing parameters 425 may be created and stored in the
audio parameter memory 460.
[0046] The processing parameters 425 may define the type and degree
of one or more processes to be performed on the digitized ambient
sound or upon any secondary audio feed. For example, the processing
parameters 425 may define filtering by a low pass filter with a
particular cut-off frequency (the frequency at which the filter
start to attenuate) and slope (the rate of change of attenuation
with frequency) and/or compression using a particular function
(e.g. logarithmic). For further example, the processing parameters
425 may define the way in which a secondary audio feed is overlaid
or combined with the digitized ambient sound. The number and format
of the processing parameters 425 may vary depending on the type of
audio processing to be performed.
[0047] The audio processing function 410 may be defined, in part,
based on analysis of the ambient sound by an analysis function 420,
which may be implemented by the same processor, or a different
processor, as the audio processing function 410. The analysis
function 420 may analyze the digitized ambient sound to determine,
for example, an overall (i.e. across the entire audible frequency
spectrum) loudness level or the loudness level within particular
frequency bands. For further example, the analysis function 420 may
transform the digitized ambient sound and/or the digitized sound
output from the audio processing function 410 into the frequency
domain using, for example, a windowed Fourier transform. The
transformed sound may then be analyzed to determine the
distribution of the ambient sound within the audible frequency
spectrum and/or to detect the presence of dominant sounds at
particular frequencies. The analysis function 420 may perform other
analysis to determine other characteristics of the digitized
ambient sound.
[0048] A portion of the processing parameters 425 for the audio
processing function 410 may define processes dependent on the
analysis of the ambient sound. For example, a first processing
parameter may require that the overall loudness of the processed
sound output from the time heuristic audio system 400 be less than
a predetermined value. The analysis function 420 may determine the
overall loudness of the ambient sound and the audio processing
function 410 may than provide an appropriate amount of overall
attenuation
[0049] The processing parameters 425 may be received or retrieved
from several sources. The processing parameters 425 may be received
from a user of the time heuristic audio system 400. The user may
manually enter processing parameters via a user interface 470,
which may be the user interface of a personal computing device such
as the personal computing device 120. Alternatively, a microphone
accessible to the audio processing function 410 (such as mic 210)
or a microphone (not shown) in portable computing device 300 may
provide input that is used in conjunction with the audio processing
function 410 and other processing parameters 425 to adjust the time
heuristic audio system 400.
[0050] The processing parameters 425 may be received from a device
or devices available via a computer network or otherwise available
within the cloud 130. For example, a website accessible via the
cloud 130 may list recommended sets of processing parameters for
different venues, bands, sporting events, and the like. These
processing parameters 425 may be generated, in part, based upon
feedback regarding the ambient sound from multiple time heuristic
audio systems like time heuristic audio system 140 in communication
with one another using the cloud 130. Similarly, a setting change
on one of a group of interconnected ambient and secondary audio
systems may be propagated to all.
[0051] The processing parameters 425 may be, at least in part,
location-based, which is to say the processing parameters 425 may
be associated with a current location of the time heuristic audio
system 400 as determined based upon location data 435 received, for
example, from a GPS. The current location may be a specific
location (e.g. "user's living room", "user's office", "Fenway
Park", "Chicago O'Hare Airport", etc.) or a generic location (e.g.
"sporting event", "dance club", "concert", "airplane", etc.). A
location-based parameter memory 430 may store one or more sets of
location-based processing parameters in association with data
defining respective locations. The appropriate processing
parameters may be retrieved from location-based parameter memory
430 based on location data 435 identifying the current location of
the time heuristic audio system 400.
[0052] The location data 435 may be provided by a geo-location
function 440. The geo-location function may use GPS, cell tower
signal strength, a series of relative-location calculations based
upon interconnected time heuristic audio systems 140 or some other
technique for identifying the current location. The location data
435 may be provided by the user via the user interface 470. For
example, the user may select a location from a list of locations
for which processing parameters are stored in the location-based
parameter memory 430. The location data 435, particularly for a
generic location, may be retrieved from a cloud external to the
time heuristic audio system 400. The location data 435 may obtained
by some other technique.
[0053] The one or more sets of location-based processing parameters
may have been stored in the location-based parameter memory 430
during prior visits to the corresponding locations. For example,
the user of the time heuristic audio system 400 may manually set
processing parameters for their home and save the processing
parameters in the location-based parameter memory 430 in
association with the location "home". Similarly, the user may set
and save processing parameters for other locations (e.g. "work",
"patrol", etc.). Upon returning to these locations (or to locations
defined in the negative (not "home", not "work", etc.), the
corresponding processing parameters may be automatically retrieved
from the location-based parameter memory 430.
[0054] The processing parameters 425 may be based, at least in
part, upon ambient sound, which is to say the processing parameters
425 may be associated with particular characteristics of the
ambient sound. The time heuristic audio system 400 may "listen" to
the ambient sound and learn what filter parameters the user sets in
the presence of various ambient sound characteristics. Once the
ambient sound has been characterized, the time heuristic audio
system 400 may select or suggest processing parameters 425
appropriate for the characteristics of the current ambient
sound.
[0055] For example, an audio parameter memory 460 may store one or
more audio sound profiles identifying respective sets of processing
parameters 425 to be applied to ambient audio as those processing
parameters 425 have been previously defined by the user, by a
manufacturer, by a supervisor, or by an organization of which a
wearer is a member for use in a particular environment or
situation. Each stored audio sound profile may include
characteristics such as, for example, frequencies to attenuate or
increase in volume, instructions to emphasize sounds that already
stand out from the overall ambient sound environment (e.g.
gunshots, footsteps, dogs barking, human voices, whispers, etc.)
while deemphasizing (e.g. decreasing the overall volume) other
ambient sounds, elements of sound to emphasize, aspects to
superimpose over ambient audio or identifications of databases and
algorithms from which to draw audio for superimposition over
ambient audio, locational feedback algorithms for emphasizing
locations of certain sounds or frequency ranges, sources of live
audio to superimpose over ambient sound or other, similar
profiles.
[0056] An ambient sound characterization function 450, which may
work in conjunction with or in parallel to the analysis function
420, may develop an ambient sound profile of the current ambient
sound. The profile determined by the ambient sound characterization
function 450 may be used to retrieve an appropriate sound profile,
including the associated processing parameters 425 from the audio
parameter memory 460. This retrieval may rely in part upon the
location data 435 and location-based parameter member 430. These
stored ambient sound profiles and processing parameters 425 may
direct the system 140 to operate upon ambient sound and/or
secondary audio sources in a particular fashion.
[0057] The one or more sets of processing parameters 425 making up
one or more audio sound profiles may have been stored in the audio
parameter memory 460 during prior exposure to ambient sound having
particular profiles. The processing parameters 425 may direct the
way in which ambient sound and secondary audio are treated by the
time heuristic audio system 400. These settings may be
across-the-board settings such as overall maximum or minimum volume
or may be per-audio-source settings such that ambient audio has
reverb added, while secondary audio is clean. Similarly, ambient
and/or secondary audio may be "spatialized" (made to sound as
though they are present at a particular location or distance from
the hearer) based upon these processing parameters 425. More detail
is provided below.
[0058] For example, the user of the time heuristic audio system 400
may manually set processing parameters 425 during a visit to a
dance club. These processing parameters 425 may be saved in the
audio parameter memory 460 in association with the profile of the
ambient sound in the dance club. The processing parameters 425 may
be saved in the audio parameter memory 430 in response to a user
action, or may be automatically "learned" by the active time
heuristic audio system 400. Upon encountering similar ambient
audio, the appropriate processing parameters 425 may be
automatically retrieved from the audio parameter memory 460.
[0059] This heuristic learning process may take place based upon
time-based data 455 received by a time-based heuristic learning and
characterization function 458. The time-based data may be provided
from a calendar, an email, or a text-based source available to a
personal computing device 120, when compared with a clock, for
example a clock of the personal computing device 120. The
time-based data 455 may take the form of a calendar event
indicating that a user is present at a particular location, event,
or premises. The time-based data 455 may be used by the time-based
heuristic learning and characterization function 458 in one of two
ways.
[0060] First, the time-based heuristic learning and
characterization function 458 may make a determination whether the
user is present at a particular location, event, or premises based
upon the present time or available sources of the user's current
location, event, or premises. The time-based heuristic learning and
characterization function 458 may, if the user has manually altered
the processing parameters 425 of the audio processing function 410,
take note of the current time, the associated current location,
event, or premises in the audio parameter memory 460. In this way,
if the user makes the same manual alteration to the processing
parameters 425 more than a threshold number of times, the audio
parameter memory may be updated to reflect that those processing
parameters 425 are to be used each time the time-based data 455
indicates that the time has changed to the associated time or that
the user is present in the location, event, or premises.
[0061] Second, the time-based heuristic learning and
characterization function 458 may access the present time from, for
example, a personal computing device 120 clock, or may access one
or more data repositories for a user's present location, event
attendance, or premises presence periodically or as a user changes
locations. Based upon this time-based data 455, the audio
processing function 410 may store instructions--user input or
learned heuristically--to use a particular set of processing
parameters 425. In this way, the time-based heuristic learning and
characterization function 458 may "learn" relevant times and places
which, based upon time-based data, may be used to automatically
select audio processing parameters 425 for ambient sound and/or
secondary audio.
[0062] Although location data is distinct from the time-based data
455, the heuristic learning and characterization function 458 may
also "learn" or rely upon the geo-location function 440 or location
data 435 to select a particular set of processing parameters 425.
Specifically, the function 458 may rely upon all available data
including both time-based data 455 and location data 435 when
making determinations of locations of individuals. Nonetheless,
these two types of data are expressly distinct from one another as
used herein.
[0063] While FIG. 4 depicts the audio parameter memory 460 and the
location-based parameter memory 430 separately, these may be a
common memory that associates each stored set of processing
parameters 425 with a location, with an ambient sound profile, or
both. Thus, one or both of audio parameters and location-based
parameters may be taken into account when selecting or suggesting
processing parameters 425 for an time heuristic audio system
400.
[0064] An adder 480 may add a secondary audio feed to the output
from the audio processing function 410 to produce the digitized
processed sound. The secondary audio feed may be received by the
time heuristic audio system 400 from an external source via a
wireless communications link and the secondary audio may be
processed by the audio processing function 410 before being added
to the ambient sound. For example, a user at a sporting event may
receive a secondary audio feed of a sportscaster describing the
event, which is then superimposed on the processed ambient sound of
the event itself. This superimposition of secondary audio may be,
in part, controlled by time-based data 455 (e.g. tickets to a
sporting event stored in a user's email account) indicating that
the user is present or plans to be present at the sporting
event.
[0065] The depiction in FIG. 4 of the time heuristic audio system
400 as a set of functional blocks or elements does not imply any
corresponding physical separation or demarcation. All or portions
of one or more functional elements may be located within a common
circuit device or module. Any of the functional elements may be
divided between two or more circuit devices or modules. For
example, all or portions of the audio processing function 410, the
analysis function 420, and the adder 480 may be implemented within
a time heuristic audio system packaged within an earbud or other
housing configured to interface with a user's ear. The ambient
sound characterization function 450, the audio parameter memory 460
and the location-based parameter memory 430 may be distributed
between time heuristic audio system and a personal computing device
coupled to the time heuristic audio system by a wireless
communications link.
[0066] Next, FIG. 5 shows a functional block diagram of a time
heuristic audio system 500. The system 500 is shown in functional
blocks which may or may not conform to individual elements of
physical hardware. The system 500 is made up of the audio
processing system 510 and the personal computing device 520. While
shown as distinct from one another, depending on the
implementation, some or all aspects of the personal computing
device 520 may be implemented within the audio processing system
510. Some or all of elements of the functional block diagram may be
encompassed within the audio processing system 110 or within the
personal computing device 120. That is to say, the functions and
processing described with reference to FIG. 5 may take place in
whole or in part in one or both of these devices, with the final
sound being delivered to one or more speakers within the audio
processing system 110.
[0067] The personal computing device 520, which may be personal
computing device 120, includes time-based data sources 535, a clock
545, a time-based heuristic learning and characterization function
558, a time-based characterization memory 559, and a processing
parameter memory 560. The audio processing system 510, which may be
audio processing function 110, processes ambient and/or secondary
audio as directed by processing parameters used to guide that
processing.
[0068] The user or external input 502 is manual or selected data
identifying a particular one or more processing parameters to be
used by the audio processing system 510. The time-based heuristic
learning and characterization function 558 is a function for both
learning processing parameters associated with particular
time-based data 555 and for instructing the audio processing system
510 to use those learned processing parameters when processing
audio.
[0069] The time-based data sources 535 are sources from which
time-based data 555 is drawn. Examples of time-based data sources
535 include calendars, text messaging clients and email clients on
the personal computing device 520. Other time-based data sources
535 may include cloud-based sources such as email accounts with
data stored on the web, web-accessible calendars, websites, and
remotely-stored documents that include time-based data 555.
[0070] Time-based data sources 535 include other sources of
time-based data 555 such as documents or hyperlinks included with
emails, text messages, or instant messages. The time-based data
555, such as a portable document format (PDF) ticket attached to an
email or an embedded hyperlink in an email, may indicate the time
of an event so that the system may be aware of the user's presence
at the event. Further, the PDF may also include information
pertaining to a particular artist or series of artists appearing
at, for example, a concert. Or, the PDF may include information
indicating the name of a stadium or venue where a sporting event or
performance is taking place. Still further alternatively, the PDF
(or other time-based data source 535) may indicate that the user is
watching or planning to watch a particular movie (or a particular
theater for watching the movie) for which associated processing
parameters 525 exist, and that maybe loaded from processing
parameter memory 560.
[0071] Time-based data sources 535 may include machine learning
capabilities such that less-specific cues may be required. For
example, a text or instant message on a particular date with the
keyword "U2" identifying a popular Irish band of that name or, more
specifically, using machine language parsing techniques on a full
phrase like "see you at U2 tonight!" may be cross-referenced using
Internet data to determine that there is a U2 concert later on the
day of receipt of that text or instant message. Thus, from this
data, the system may extract time-based data 555 that indicates
that a particular individual is likely going to be present at that
concert and may adjust audio processing parameters according to
that time-based data 555 during the show.
[0072] The time-based data sources 535 may generate time-based data
555 that is used in conjunction with the ambient sound
characterization function 450 to select relevant processing
parameters. For example, time-based data 555 may be used to
determine that the system is present at a particular concert with a
known start time. However, music may not actually begin exactly at
the start time. So, the ambient sound characterization function 450
may be use in conjunction with the time-based data 555 to select
processing parameters for the concert, but to await implementation
of the concert-based processing parameters until the ambient sound
characterization function 450 indicates that music has actually
begun. Until music has begun, the system may sit in a wait state
using default processing parameters awaiting the commencement of
music. This same type of wait state may be used in various types of
time-based data awaiting relevant ambient sound characterization by
the ambient sound characterization function 450.
[0073] Time-based data sources 535 may include other mobile
applications operating on the personal computing device 520 that
can generate or have access to time-based data 555. For example, a
mobile application such as Uber.RTM. by which a user requests a
ride to a particular location may provide time-based data including
a pick-up or drop-off location "pin" that identifies a place and an
associated time. Time-based data 555 (and potentially location
data) may be drawn from the mobile application to be used by the
time-based heuristic learning and characterization function 558 to
select relevant processing parameters.
[0074] These types of information may be used, for example, by the
time-based characterization memory 559 to access parameters in the
processing parameter memory 560 associated with a particular
artists, event, or venue. In this way, the time-based data 555 may
be more than merely a time/location or a time/activity combination,
but may further include additional data that is relevant to audio
processing parameters. Processing parameters 525 stored in
processing parameter memory 560 may be user-set, set by an artist,
set by a venue, set by an audio technician for a particular artist,
venue, or event, or may be crowd-sourced such that if a sufficient
number of users of the system in a location, at a venue, listening
to an artist, or viewing a sporting event select a particular set
of processing parameters 525 (manually or automatically) the same
set of processing parameters 525 may be identified by the
time-based characterization memory 559 as associated with the time,
event, artist, venue, or location.
[0075] The time-based data 555 may be or include the likelihood
that a user of the system is sleeping or will be sleeping soon
regardless of any particular location. Based upon prior user
activity or likely user desires, the system may automatically
access processing parameters 525 that lower the overall volume of
ambient sound or otherwise cancel ambient sound to aid a user in
sleeping or to avoid unwanted external audio that may disturb
sleeping patterns. In such a situation, the time based data 555 may
be or include a user's prior sleep patterns as input by a user or
as determined over time based upon settings of the system or of
personal computing devices in communication with the system. For
example, a lack of interaction with the system or a personal
computing device from certain hours may suggest sleep and, over
time, be learned by the system as associated with a typical sleep
pattern for the user. Audio processing parameters 525 may be
selected accordingly.
[0076] Time-based data 555 indicating that a particular artist (or
event-type--e.g. football, baseball, hockey, etc.) and at a
particular venue or location may indicate to the time-based
characterization memory 559 that a particular set of processing
parameters 525 should be selected from the processing parameter
memory 560. The processing parameter memory 560 may, in part, be or
be formed by processing parameters 525 provided by third parties
such as concert venues, event management companies, artists,
sporting teams and similarly-situated groups for which specific
processing parameters 525 may be relevant.
[0077] In some cases, these processing parameters 525 may identify
one or more secondary feeds such as a live feed from an audio
technician's equipment directly to a user's ears (rather than
ambient audio for music), a particular audio set for a movie or
augmentation of ambient audio for a movie, a sportscaster's live
broadcast super-imposed over the ambient sound of a stadium at a
sporting event, and other, similar secondary audio sources.
[0078] The clock 545 provides the current time 548 on a periodic
basis or upon request.
[0079] The time-based characterization memory 559 stores data
pertaining to user or external input 502 that may be used to guide
future automatic selection of processing parameters based upon
time-based data 555. The time-based characterization memory 559 may
also store the identity, a name for, a memory location of, or other
data pertaining to or identifying one or more processing parameters
selected in relationship to a particular set of time-based data
555. In this way, over time, the time-based characterization memory
559 may come to store a number of associations between processing
parameters and particular sets of time-based data 555.
[0080] Further, if multiple processing parameters are identified as
relevant based upon a given set of time-based data 555, the system
may enable a process of manual interaction with the personal
computing device 120 whereby a user can select one or more of those
processing parameters for implementation. This process may begin
with an audio prompt to a user of the audio processing system 110
that indicates that interaction with the personal computing device
120 is required or, alternatively, may begin with a visual cue on
the personal computing device 120. Auditory response or other
non-visual responses, such as voice recognition in response to
audio identification of associated processing parameters may be
available to a user. In this way, a user may hear, for example, the
names of processing parameter sets 1, 2, and 3, then speak audibly
a selection of 1 and 3, whereby those two sets of processing
parameters are selected. Exterior buttons, either on the personal
computing device 120 or the audio processing system 110 may be
mapped to the selection of particular processing parameters
identified audibly. Similarly, specific interactions with exterior
buttons, such as double-clicks or short, then long, clicks of a
button, may indicate a particular response to the identification of
a processing parameter set.
[0081] As discussed above, the processing parameter memory stores
processing parameters, like processing parameters 525, that
instruct an audio processing system 510 in how to process a
selected set of ambient and/or secondary audio sources.
[0082] As discussed more fully below, the user or external input
502 may be provided to the time-based heuristic learning and
characterization function 558 to, at least in part, inform the
function 558 in what processing parameters a user desires. This
input may, for example, be the manual selection of a pre-determined
set of processing parameters, or may be the manual selection of a
series of individual processing parameters to, thereby, manually
create a set. This user or external input 502 may merely identify a
set of processing parameters already stored in the processing
parameter memory 560 or may include external input such as an
identification of processing parameters provided by a third party
as desirable.
[0083] This user or external input 502 may be stored by the
function 558 in the time-based characteristic memory 559, with the
present time 548, as provided by the clock 545, simultaneously
noted and stored in the memory 559. In addition, time-based data
555 provided from time-based data sources 535 may also be noted and
stored in the memory 559. In this way, details regarding the
selected processing parameters, the present time 548, and the
associated time-based data 555 (if any) may be simultaneously
stored in memory 559 for later use in automatically selecting
processing parameters.
[0084] The selected processing parameters 525 may be obtained from
the processing parameter memory 560 and provided to the audio
processing system 510 for operation upon any sources of sound in
505. Once acted upon by the audio processing system 510, using the
processing parameters 525, the processed sound out 515 is output by
the audio processing system 510.
[0085] Once the time-based heuristic learning and characterization
function 558 has "learned" some time-based data 555 that is
consistently used to select one or more particular sets of
processing parameters, user or external input 502 may no longer be
required. Instead, time-based data sources 535 may be periodically
consulted in conjunction with time 548 from the clock 545 to
determine that the time, date and/or day is the same or that user
is at the same event, premises, or location where the user manually
selected a set of processing parameters as described above. If the
time-based data 555 and the time 548 correspond to the prior
settings, the time-based heuristic learning and characterization
function 558 may refer to the time-based characterization memory
559 to obtain relevant processing parameters associated uniquely
with the time-based data 555 and the time 548 from the processing
parameter memory 560. Thereafter, these processing parameters 525
may be provided to the audio processing system 510 without any user
or external action.
[0086] Description of Processes
[0087] Referring now to FIG. 6, a flow chart of a method 600 for
creating a time heuristic audio control is shown. The process
begins at 605 and ends at 695. The process 600 may occur many times
as user input or other external input altering processing
parameters is received. The process 600 results in the storage of
the identity of time-based data and associated processing
parameters that may be linked so as to be automatically selected at
later times when the associated time-based data is received.
[0088] After the start 605, a determination is made whether a
processing parameter has been selected at 615. If not ("no" at
615), then the process ends at 695.
[0089] If so ("yes" at 615), time-based data is accessed at 620.
This may be accessing a calendar, email, a short message service,
external sources of time-based data such as web-based email,
calendars, or similar sources. This may involve determining whether
any of the time-based sources indicates that a user of the system
is presently at an event, location, or premises or, alternatively,
may be a determination of the present time, day, and/or date so
that it may, optionally, later be associated with the processing
parameter changes that have been made repeatedly.
[0090] This time-based data is accessed so that the system may
store the time based data in conjunction with the selected
processing parameters at 630. This data may be stored, as described
briefly above, in the time-based heuristic memory 559 (FIG. 5).
[0091] Next, a determination is made, using data stored in the
time-based heuristic memory 559, whether there have been multiple
selections of the same (or essentially the same) processing
parameters when relevant time-based data is present at 635. This
determination may merely be comparing a set of parameters to
time-based data comprised of the present date/time (e.g. 10:00 am),
to the present time and day (e.g. 10:00 am on a Tuesday), to the
present time and day and day of the month (e.g. 10:00 am on the
second Tuesday of the month), to a specific time and day (e.g.
10:00 am on a holiday morning), or to a specific event, premises,
or location identified in time-based data from a time-based data
source such as a calendar, email, a text message, or an instant
message.
[0092] If there are multiple selections of the same processing
parameters in conjunction with associated time-based data (e.g.
always at 10:00 am on the second Tuesday of the month or always
when the user is present in a "meeting" with a certain person),
then the processing parameters may be stored as automatic
processing parameters to select at 640 when the same time-based
data is present in the future. For example, the processing
parameters may be selected automatically every 10:00 am on the
second Tuesday of the month or when the user is present in a
"meeting" with a certain person.
[0093] The storage automatic selection of processing parameters at
640 may be relatively sophisticated in that it may store the
processing parameters in conjunction with time-based data that is
defined as one or more if/then or case statements such that when
each element is appropriately met, the automatic selection of
processing parameters may take place. Over time, with further
refinement, the automatic selection definition may be altered so as
to conform to recent changes by a user.
[0094] Thereafter, the process ends at 695. Subsequent manual
changes or external input of processing parameters may cause the
process to begin again as associated new time-based data may be
introduced (e.g. another meeting, a different time, a different
location) for which other processing parameters may be desired by a
user. In effect, this process may occur continuously, with the
system continuously monitoring for new time-based data and
associated processing parameters that may be "learned"
heuristically and stored for later use.
[0095] Referring now to FIG. 7, a flow chart of a method for
altering audio processing parameters in response to a time
heuristic audio control is shown. The process 700 begins at 705 and
ends at 795 once audio processing has begun using selected
processing parameters. The process 700 may be initiated
periodically or based upon identification of time-based data that
may cause a change in the selection of processing parameters.
[0096] After the start 705, the time-based data is accessed at 710
by the time heuristic learning and characterization function 558 so
that the time-based data may be used to determine if any changes to
the processing parameters should be made. This may be accessing a
time-based data source such as a calendar, email, or instant
messaging service in order to access or obtain time-based data.
[0097] Next, the current time is accessed at 720. This may include
accessing the current time, day, date, any holiday data or
externally-available data that is not specific to an individual
calendar, but is or may be relevant to the time heuristic learning
and characterization function 558 in determining whether new
processing parameters should be used.
[0098] Next, the time heuristic learning and characterization
function 558 determines whether there are any current time-based
processing parameters at 725. This process entails determining if
any of the time-based data accessed at 710 matches the current time
accessed at 720 such that new processing parameters should be used
for processing ambient and any secondary audio. If not ("no" at
725), then the process ends at 795.
[0099] If so ("yes" at 725), then the processing parameters
associated with the current time-based data are identified at 730.
This may involve accessing the time-based characterization memory
559 to identify the processing parameters associated with the
particular time-based data. Then, the processing parameters maybe
identified within the processing parameter memory 560 based upon
the data in the time-based characterization memory 559.
[0100] Once the processing parameters have been identified at 730,
they are transmitted to the audio processing system 510 at 740 so
that audio processing may begin based upon those processing
parameters identified.
[0101] The audio processing system 510 and/or the personal
computing device 520 may receive user interaction indicating that
the user has elected to change the automatically-selected
processing parameters at 745. Though shown as immediately following
transmission of the processing parameters, the audio processing
system 510 may first begin performing audio processing using the
parameters and then accept changed processing parameters from a
user. However, the option to alter those processing parameters
exists from the moment they are automatically selected and
transmitted.
[0102] If a user makes a change to processing parameters ("yes" at
745), then the changes may be stored in the time-based
characterization memory at 750. These changes, particularly if they
are made more than one time, may form the basis of updates to the
processing parameters associated with a particular set of
time-based data.
[0103] After any changes are stored at 750, or if no changes are
detected ("no" at 745), the audio processing system 510 processes
ambient and/or secondary audio sources as directed by the
processing parameters selected based upon the time-based data at
760. At any point, a user may manually alter these processing
parameters, but, these processing parameters may be automatically
selected in response to relevant time-based data as directed by the
time heuristic control system.
[0104] The process then ends at 795, but may continue to be run
periodically or in response to new time-based data indicating that
processing parameters should or may change.
[0105] Closing Comments
[0106] Throughout this description, the embodiments and examples
shown should be considered as exemplars, rather than limitations on
the apparatus and procedures disclosed or claimed. Although many of
the examples presented herein involve specific combinations of
method acts or system elements, it should be understood that those
acts and those elements may be combined in other ways to accomplish
the same objectives. With regard to flowcharts, additional and
fewer steps may be taken, and the steps as shown may be combined or
further refined to achieve the methods described herein. Acts,
elements and features discussed only in connection with one
embodiment are not intended to be excluded from a similar role in
other embodiments.
[0107] As used herein, "plurality" means two or more. As used
herein, a "set" of items may include one or more of such items. As
used herein, whether in the written description or the claims, the
terms "comprising", "including", "carrying", "having",
"containing", "involving", and the like are to be understood to be
open-ended, i.e., to mean including but not limited to. Only the
transitional phrases "consisting of" and "consisting essentially
of", respectively, are closed or semi-closed transitional phrases
with respect to claims. Use of ordinal terms such as "first",
"second", "third", etc., in the claims to modify a claim element
does not by itself connote any priority, precedence, or order of
one claim element over another or the temporal order in which acts
of a method are performed, but are used merely as labels to
distinguish one claim element having a certain name from another
element having a same name (but for use of the ordinal term) to
distinguish the claim elements. As used herein, "and/or" means that
the listed items are alternatives, but the alternatives also
include any combination of the listed items.
* * * * *