U.S. patent application number 15/132825 was filed with the patent office on 2016-08-11 for method for augmenting hearing.
The applicant listed for this patent is Symphonic Audio Technologies Corp.. Invention is credited to Aaron Alexander Selig, Varun Srinivasan.
Application Number | 20160234606 15/132825 |
Document ID | / |
Family ID | 51729020 |
Filed Date | 2016-08-11 |
United States Patent
Application |
20160234606 |
Kind Code |
A1 |
Selig; Aaron Alexander ; et
al. |
August 11, 2016 |
METHOD FOR AUGMENTING HEARING
Abstract
One variation of a method for augmenting sound includes: at a
mobile computing device and a connected audio output device,
outputting a tone in a hearing test; based on a response to the
tone entered by a user, generating a hearing profile for the user
and corresponding to the mobile computing device and the audio
output device; receiving an audio signal; qualifying the audio
signal as a particular audio type from a set of audio types;
selecting, from a set of sound profiles, a particular sound profile
corresponding to the particular audio type; at the mobile computing
device, transforming the audio signal into a processed audio signal
according to the particular sound profile and the hearing profile
of the user; and outputting the processed audio signal at the
connected audio output device.
Inventors: |
Selig; Aaron Alexander; (San
Francisco, CA) ; Srinivasan; Varun; (San Francisco,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Symphonic Audio Technologies Corp. |
San Francisco |
CA |
US |
|
|
Family ID: |
51729020 |
Appl. No.: |
15/132825 |
Filed: |
April 19, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14178067 |
Feb 11, 2014 |
9344815 |
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15132825 |
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61763182 |
Feb 11, 2013 |
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61867449 |
Aug 19, 2013 |
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61880377 |
Sep 20, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/123 20130101;
H04R 25/50 20130101; A61B 5/6898 20130101; H04R 2225/83 20130101;
H04M 1/72569 20130101; H04M 1/72591 20130101; H04R 2460/03
20130101; H04R 2460/07 20130101; H04R 25/70 20130101; H04R 29/008
20130101; H04R 2225/41 20130101; A61B 2560/0242 20130101; H04R
2225/55 20130101 |
International
Class: |
H04R 25/00 20060101
H04R025/00 |
Claims
1. A method for augmenting sound, comprising: at a mobile computing
device and a connected audio output device, outputting a tone in a
hearing test; based on a response to the tone entered by a user,
generating a hearing profile for the user and corresponding to the
mobile computing device and the audio output device; receiving an
audio signal; qualifying the audio signal as a particular audio
type from a set of audio types; selecting, from a set of sound
profiles, a particular sound profile corresponding to the
particular audio type; at the mobile computing device, transforming
the audio signal into a processed audio signal according to the
particular sound profile and the hearing profile of the user; and
outputting the processed audio signal at the connected audio output
device.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. application Ser.
No. 14/178,067, filed 11 Feb. 2014, which claims the benefit of
U.S. Provisional Application No. 61/763,182, filed on 11 Feb. 2013,
U.S. Provisional Application No. 61/867,449, filed on 19 Aug. 2013,
and U.S. Provisional Application No. 61/880,377, filed on 20 Sep.
2013, all of which are incorporated in their entireties by this
reference.
TECHNICAL FIELD
[0002] This invention relates generally to the field of hearing
augmentation, and more specifically to a new and useful method for
augmenting hearing in the field of hearing augmentation.
BACKGROUND
[0003] Approximately 12% of the population in the United States
suffers from significant hearing loss. 30-40% of people over the
age of 65, 14% of people between the ages of 45-64, and 15% of
children between the ages of 6-19 having a measurable degree of
hearing loss in at least one ear. However, though hearing aids can
offer dramatic improvement in hearing for people with hearing loss
in specific settings, hearing aids are typically limited to single
hearing profiles and therefore fail to adequately augment user
hearing in multiple use scenarios and during varying physical
settings.
[0004] Therefore, there is a need in the field of hearing
augmentation to create a new and useful method for augmenting
hearing. This invention provides such a new and useful method.
BRIEF DESCRIPTION OF THE FIGURES
[0005] FIG. 1 is a flowchart representation of a method of one
embodiment of the invention;
[0006] FIG. 2 is a flowchart representation in accordance with one
variation of the method;
[0007] FIG. 3 is a flowchart representation in accordance with one
variation of the method;
[0008] FIG. 4 is a graphical representation in accordance with one
variation of the method; and
[0009] FIG. 5 is a flowchart representation in accordance with one
variation of the method.
DESCRIPTION OF THE EMBODIMENTS
[0010] The following description of the embodiments of the
invention is not intended to limit the invention to these
embodiments, but rather to enable any person skilled in the art to
make and use this invention.
1. Method and Applications
[0011] As shown in FIG. 1, a method for augmenting sound includes:
at a mobile computing device and a connected audio output device,
outputting a tone in a hearing test in Block S102; based on a
response to the tone entered by a user, generating a hearing
profile for the user and corresponding to the mobile computing
device and the audio output device in Block S104; receiving an
audio signal in Block S110; qualifying the audio signal as a
particular audio type from a set of audio types in Block S120;
selecting, from a set of sound profiles, a particular sound profile
corresponding to the particular audio type in Block S130; at the
mobile computing device, transforming the audio signal into a
processed audio signal according to the particular sound profile
and the hearing profile of the user in Block S140; and outputting
the processed audio signal at the connected audio output device in
Block S150.
[0012] As shown in FIG. 3, one variation of the method S100 for
augmenting sound includes: at an audio device, receiving a hearing
profile from a mobile computing device in Block S106, the hearing
profile corresponding to a user and generated on the mobile
computing device; receiving an audio signal from the mobile
computing device in Block S110; qualifying the audio signal as a
particular audio type from a set of audio types in Block S120;
selecting, from a set of sound profiles, a particular sound profile
corresponding to the particular audio type in Block S130;
transforming the audio signal into a processed audio signal
according to the particular sound profile and the hearing profile
of the user in Block S140; and substituting the audio signal for
the processed audio signal at an output of the audio device in
Block S150.
[0013] Generally, the method S100 functions to process (e.g.,
manipulate, change) an audio signal substantially in real-time
according to a known hearing ability of a user and a sound profile
specific to a characteristic, type, and/or origin of the audio
signal, thereby dynamically adapting an output of an audio device
specifically for the user across various listening scenarios. The
method S100 can further process the audio signal according to an
audio output profile of the audio device and/or a (mobile)
computing device employed by the user and/or real-time factors that
affect sound perception, such as location, acoustics of a room,
time of day, activity or behavior of a user, a demographic of the
user, etc. The method S100 can thus output an augmented audio
signal substantially in real-time and tailored to an immediate
hearing need of the user.
[0014] Once a hearing profile for the user is generated from a
hearing test, the method S100 collects an audio signal in real
time, qualifies the audio signal to determine a type or component
of sound in the audio signal, selects a sound profile based on the
type of audio signal (and/or various user-, location-, and/or
device-related variables), and outputs an augmented audio signal
based on the sound profile, the original audio signal, and the
user's hearing profile in order to augment the user's perception of
(details of) the audio signal. In particular, the method S100 can
adjust the augmented audio output according to a type of audio
signal and/or a current setting, behavior, action, and/or need of
the user by selecting a sound profile, from a set of available
sound profiles, most closely matched to the current audio signal
type, setting, behavior, action, and/or need of the user and/or by
adjusting a sound profile to substantially conform to the current
audio type, setting, behavior, action, and/or need of the user. For
example, the method S100 can process live sound, such as recorded
through a microphone in the user's mobile computing device (e.g.,
smartphone, tablet) or transmitted to the users mobile computing
device in a phone or video-conferencing call. The method S100 can
additionally or alternatively process prerecorded audio files, such
as local or streamed digital music files (e.g., MP3) or audio
components of digital video files. However, the method S100 can be
applied to any other real-time audio, prerecorded audio, streaming
audio, or other digital or analog audio signal.
[0015] The method S100 can therefore be implemented in various
settings, such as to aid the user in a face-to-face conversation
with a single person or a small group of people in a closed room,
to aid the user in a face-to-face conversation with multiple people
in a crowded and/or boisterous space (e.g., while at dinner in a
crowded restaurant), to aid the user in hearing a speech or lecture
in an auditorium, or to aid the user in holding a phone
conversation with a person in a quiet room or while walking down a
busy street on a windy day. In further examples, the method S100
can to aid the user in hearing audio broadcast from a television,
to aid the user in hearing higher-quality sound while attending a
concert, opera, symphony, or other performance, or to augment the
user's listening experience while playing music through headphone
connected to an MP3 player, smartphone, etc. However, the method
S100 can be applicable to any other scenario to augment the user's
hearing and/or sound experience.
[0016] The method S100 can be implemented by one or more computer
systems, such as a cloud-based computer system (e.g., Amazon EC3),
a mainframe computer system, a grid-computer system, or any other
suitable computer system. In one example implementation, the method
S100 is implemented by a native application executing on a mobile
computing device, such as a smartphone or tablet. For example, a
smartphone (i.e., mobile computing device) can implement the method
S100 in the form of a native hearing augmentation application (or
"app") that generates a hearing profile of the user locally with a
hearing test, receives local sounds through a microphone
incorporated in the smartphone or in a headset or headphones worn
by the user, adjusts the received sounds according to the user's
hearing profile and the type of audio signal, and outputs the
processed audio signal through the headset or headphones. In
another example implementation, the method S100 is implemented
through software executing on embedded circuitry (e.g., a processor
or microcontroller) incorporated into an audio device, such as a
standalone speaker, a home or car stereo system, a headset, or a
set of headphones. In yet another example implementation, Blocks of
the method S100 are implemented by a remote server in cooperation
with a native application executing on a mobile computing device.
In another example implementation, Blocks of the method S100 are
implemented on a peripheral device arranged between an audio output
of the user's mobile computing device (e.g., smartphone, tablet)
and an input of an audio device (e.g., headset, set of headphones)
such that the peripheral device processes an audio signal output
from the mobile computing device and passes the processed audio
signal to the connected audio device. The computer system can also
incorporate a user interface through which the user can input
responses to musical signals, review a hearing profile, enter
demographic or other personal information, upload music or audio
files, or enter, access, or review any other data or information.
The use interface can be accessible through a web browser or
through a native application executing on a (mobile) computing
device, such as a laptop computer, a desktop computer, a tablet, a
smartphone, a personal data assistant (PDA), a personal music
player, etc. Generally, the audio device can include any device
that outputs sound, such as a pair of headphones, a speaker, or a
mobile phone. The computing device can include any device that
processes a digital signal, such as a headset incorporating a
microprocessor, a smartphone, or a tablet. However, the audio
device, the peripheral device, and/or the computing device can be
any other suitable type of device and can be discrete and/or
physically coextensive (i.e., embodied in the same device).
[0017] In the implementation in which Blocks of the method S100
execute on a mobile computing device, the mobile computing device
can execute Blocks S102 and S104 to test the user's hearing and to
generate a hearing profile for the user accordingly. In particular,
the method S100 can implement Blocks S102 and S104 to generate the
user's hearing profile locally on the user's mobile computing
device and/or the connected audio device such that an audio output
profile of the mobile computing device and/or an audio output
profile of a connected audio device are inherent in the hearing
profile. Thus, when the audio signal is subsequently processed at
the mobile computing device according to the hearing profile, the
processed audio signal can compensate for the audio output profile
of the mobile computing device and/or the audio output profile of
the connected audio device, as these are inherent in the user's
hearing profile. Thus, by generating the user's hearing profile
locally, the method S100 can output a processed audio signal to
augment the user's listening experience without identifying or
accessing specific output profiles for the mobile computing device
and/or for the audio device.
[0018] Similarly, in the implementation in which Blocks of the
method S100 execute on a peripheral device (or locally on an audio
device) connected to a mobile computing device, the peripheral
device (or the connected audio device) can execute Block S106 to
download the user's hearing profile from the mobile computing
device. In this implementation, the mobile computing device can
execute a method or technique like that of Blocks S102 and S106 to
generate a hearing profile for the user and specific to the mobile
computing device, the peripheral device, and/or the connected audio
device, and the peripheral device (or the connected audio device)
can thus download the hearing profile from the mobile computing
device once the hearing profile is complete and available from the
mobile computing device. Thus, in these implementations, the method
S100 can generate the processed audio signal that inherently
compensates for audio output profiles unique to the mobile
computing device, the peripheral device, and/or the connected audio
device by implementing a user hearing profile generated locally and
specific to the combination mobile computing device, peripheral
device, and/or connected audio device.
2. Hearing Profile
[0019] Block S102 of the method S100 recites, at a mobile computing
device and a connected audio output device, outputting a tone in a
hearing test. Block S104 of the method S100 further recites, based
on a response to the tone entered by a user, generating a hearing
profile for the user and corresponding to the mobile computing
device and the audio output device. Generally, Blocks S102 and S104
of the method S100 implement an abbreviated (i.e., shortened)
hearing test locally on the user's mobile computing device to
generate a hearing profile specific to the mobile computing device
(and the connected audio device) for the user.
[0020] In one implementation, Blocks S102 and S104 cooperate to:
output a first audible tone including a first frequency; record a
first volume adjustment for the first audible tone by the user;
output a second audible tone including a second frequency; record a
second volume adjustment for the second audible tone by the user;
select a particular hearing model from a set of hearing models
based on a difference between the first volume adjustment and the
second volume adjustment, each hearing model in the set of hearing
models including a hearing test result corresponding to a previous
patient; and generate the hearing profile for the user based on the
particular hearing model result, as shown in FIG. 5.
[0021] In this implementation, Blocks S102 and S104 can generate a
hearing profile that characterizes a user's hearing ability by
testing the user's ability to hear a select subset of frequencies
in the audible range, selecting a particular hearing test result
from another user (or patient) who exhibits substantially similar
hearing abilities at the select subset of frequencies, and applying
data from the particular hearing test result to the user to fill in
gaps in the hearing test at untested frequencies. In particular,
Block S104 can collect a limited amount of hearing ability data
from a user within a limited period of time (e.g., thirty seconds),
characterize the limited amount of user hearing data, and "flesh
out" or complete an image of the user's hearing ability across (at
least a portion of) the audible range by applying preexisting
hearing ability data from one or more other users to the user based
on the characterization of the limited amount of hearing data from
the user. For example, Block S104 can match volume adjustments
entered by the user across two or more frequencies (output in Block
S102) to hearing abilities at similar frequencies captured in an
audiogram of a previous patient and then apply the audiogram of the
previous patient to the user to estimate or predict the user's
hearing abilities at other frequencies in the audible range. In
another example, Block S104 can transform volume adjustments
entered by the user across two or more frequencies into a
parametric hearing model to output a synthetic audiogram for the
user, wherein the parametric hearing model is generated from a
series of audiograms of various other patients such that the
synthetic audiogram specific to the user is a composite of multiple
audiograms of other patients. However, Blocks S102 and S104 can
apply hearing data from other patients to the user in any other way
to estimate or predict a hearing ability of the user across an
audible range given a limited amount of user hearing data captured
in a limited amount of time (e.g., less time than required to
capture a full audiogram). Furthermore, Blocks S102 and S104 can
implement any other method or technique to generate a hearing
profile for the user, such as described in U.S. Provisional
Application No. 61/763,163, filed on 11 Feb. 2013, U.S. Provisional
Application No. 61/831,796, filed on 6 Jun. 2013, U.S. Provisional
Application No. 61/867,436, filed on 19 Aug. 2013, and U.S.
Provisional Application No. 61/880,367, filed on 20 Sep. 2013, and
U.S. patent application Ser. No. 14/148,034 filed on 11 Feb. 2014,
all of which are incorporated in their entireties by this
reference.
[0022] Thus, because Block S102 outputs one or more tones of a
hearing test through the mobile computing device, the peripheral
device, and/or the connected audio device, and because Block S104
generates the user's hearing profile locally on the mobile
computing device based on audio output adjustments made by the user
in response to the one or more tones, an audio signal subsequently
processed according to the hearing profile in Block S140 can
compensate for the audio output profile(s) of the mobile computing
device, the peripheral device, and/or the connected audio device,
as these audio output profiles are inherently accommodated in the
hearing profile (i.e., the hearing profile is generated based on
user responses to tones output in Block S102, which are subject to
the audio output profiles of the mobile computing device, the
peripheral device, and/or the connected audio device).
[0023] Once the hearing profile for the user is generated, Block
S104 can further associate the hearing profile with an identifier
of the mobile computing device and an identifier of the connected
audio output device. For example, Block S104 can retrieve a unique
serial number of the mobile computing device from a memory within
the mobile computing device and then assign this unique serial
number to the user's hearing profile. In this example, Block S104
can also prompt the user to enter a type (e.g., make and model), a
serial number, or a SKU number, etc. of the connected audio device
(e.g., a headset, a pair of headphones, a speaker) into a native
hearing augmentation application executing on the mobile computing
device, and Block S104 can then assign information entered by the
user to the hearing profile. Alternatively, Block S104 can prompt
the user to scan a barcode on packaging of the audio device or
capture a picture of the audio device, and Block S104 can implement
object or character recognition to identify the audio device and to
then associate the audio device with the hearing profile
accordingly. Yet alternatively, Block S104 can prompt the user to
select an image displayed on the mobile computing device and
corresponding to the audio device or to select the audio device
from a drop-down menu.
[0024] Block S104 can also communicate directly with the audio
device to retrieve an identifier of the audio device. For example,
Block S104 can retrieve a unique Bluetooth ID or Wi-Fi ID from a
wireless-enabled audio device and then assign this unique ID to the
hearing profile. In this implementation, of the method S100 in
which the audio signal is routed from the mobile computing device
into the peripheral device and then into the connected audio
device, Block S104 can implement similar functionality to detect,
retrieve, and/or receive identification information for the
peripheral device.
[0025] Block S104 can then store the hearing profile with one or
more device-related assignments locally on the mobile computing
device, and subsequent Blocks of the method S100 can retrieve and
apply the stored hearing profile when one or more connected devices
are matched to the hearing profile. For example, Block S104 can
generate multiple hearing profiles, each specific to the mobile
computing device with one or more other connected devices (e.g.,
various headphones, headsets, peripheral devices, etc.), and
subsequent Blocks of the method S100 can selectively implement the
hearing profiles according to detected and/or confirmed connected
devices. Additionally or alternatively, Block S104 can store the
hearing profile remotely, such as within an account assigned to the
user and stored on a remote server. For example, Block S104 can
store the hearing profile in the user's account with multiple other
hearing profiles, wherein each hearing profile in the set is
associated with different devices and/or a different combination of
devices (e.g., mobile computing device, headset, set of headphones,
peripheral device, etc.), and subsequent Blocks of the method S100
can selectively download and implement hearing profiles stored with
the user's account according to detected or selected devices
routing and/or outputting the audio signal. However, Blocks S102
and S104 can function in any other way to generate, tag, and store
one or more hearing profiles for the user and one or more
combinations of mobile computing devices, peripheral devices,
and/or connected audio devices.
[0026] As shown in FIG. 3, one variation of the method S100
includes Block S106, which recites, at an audio device, receiving a
hearing profile from a mobile computing device in Block S106, the
hearing profile corresponding to a user and generated on the mobile
computing device. In this variation of the method S100 in which one
or more of Blocks S110, S120, S130, S140, and/or S150 execute on a
peripheral device, the peripheral device (e.g., an audio processing
unit arranged between an audio output of the mobile computing
device and an audio input of a set of headphones) can implement
Block S106 to retrieve a hearing profile from the mobile computing
device. For example, Block S106 can include wirelessly downloading
a hearing profile from the mobile computing device, such as over a
Wi-Fi or Bluetooth connection. Alternatively, Bock S106 can receive
the hearing profile over a wired connection, such as over an audio
jack connection between the mobile computing device and the
peripheral device. However, Block S106 can function in any other
way to retrieve a hearing profile from the mobile computing device
for application in subsequent Blocks of the method S100.
[0027] Similarly, in a variation of the method S100 in which one or
more of Blocks S110, S120, S130, S140, and/or S150 execute on a
connected audio device (e.g., a headset), the connected audio
device can similarly implement Block S106 to retrieve a hearing
profile from the mobile computing device, such as over a wired or
wireless connection.
3. Audio Signal
[0028] As shown in FIG. 1, Block S110 of the method S100 recites
receiving an audio signal. Generally, Block S110 functions to
handle audio signals from one or more sources, including live sound
(e.g., captured at a microphone integrated into the mobile
computing device, a headset, or a set of headphones or transmitted
to the mobile computing device from an external device) and
prerecorded audio, such as from music or film in playback on the
mobile computing device or played near the mobile computing
device.
[0029] In one implementation, Block S110 captures or receives live
sound through a microphone arranged within or in communication with
the user's mobile computing device. In one example, Block S110
captures sound through a microphone integrated into the mobile
computing device. In another mobile computing device, Block S110
receives sound through a microphone incorporated into the connected
audio device carried or worn or carried by the users, such as the a
headset or a set of headphones. In this example, Block S110 can
receive the audio signal via wired or short-range wireless
communication, such as over Bluetooth or Wi-Fi. In another example,
Block S110 receives sound through a microphone incorporated into a
device worn or carried by another user, such as a cellular phone or
a tablet carried by a second user during a phone call, video
conference call, or similar communication with the user. In this
example, Block S110 can receive the audio signal from the external
device via short- or long-range wireless communication, such as
over Bluetooth, Wi-Fi, or cellular communication protocol, or over
a landline or Internet connection. In particular, in this example,
Block S110 can identify an audio output from a native phone or
video conferencing application executing on the user's mobile
computing device. In another example, Block S110 receives the audio
signal recorded through and transmitted from a standalone
microphone arranged within a space occupied by the user, such as an
auditorium or an amphitheatre. Thus, Block S110 can interface with
one or more microphones in the user's mobile computing device, an
audio and/or peripheral device connected to the user's mobile
computing device, an external device, etc. to collect a live sound
or local sound in playback in the form of an audio signal.
[0030] Block S110 can also receive pre-recorded audio, such as from
a sound file (e.g., an MP3 audio file) stored locally on the mobile
computing device during playback or streamed to the mobile
computing device, such as over the Internet from an online music or
video service. For example, Block S110 can identify an audio output
from a native music or video application executing on the user's
mobile computing device.
[0031] Block S110 can further receive multiple (live) audio signals
substantially simultaneously. For example, Block S110 can collect a
first audio signal of the user's voice from a microphone
incorporated into a headset worn by the user, a second audio signal
of the voice of a second user from a microphone incorporated into a
second smartphone used by the second user, and a third audio signal
of ambient noise proximal the user from a microphone incorporated
into the user's smartphone during a phone conversation between the
user and the second user. In another example, as shown in FIG. 1,
Block S110 can collect a first audio signal from a microphone
incorporated into a set of headphones worn by the user and a second
audio signal of the user's voice from a microphone incorporated
into the user's smartphone, thereby enabling the method S100 to
generate a substantially three-dimensional soundscape (e.g., sound
image) of the space occupied by the user.
[0032] In the variation in which the peripheral device executes
various Blocks of the method S100, the peripheral device can
capture the audio signal through a microphone incorporated into the
peripheral device. Additionally or alternatively, the peripheral
device can receive the audio signal from the user's mobile
computing device, such as over a wired or wireless connection with
the mobile computing device. For example, Block S110 can receive
the audio signal over an audio output jack within the mobile
computing device. However, Block S110 can function in any other way
to receive or collect one or more audio signals.
[0033] Block S120 of the method S100 recites qualifying the audio
signal as a particular audio type from a set of audio types.
Generally, Block S120 functions to identify a type of the audio
signal. For example, Block S120 can select a particular audio
type--from a set of audio types including music, speech, and
ambient noise--and assign the selected audio type to the audio
signal. In this example, Block S120 can also identify the audio
signal as an audio component of phone call between the user's
mobile computing device and a secondary device of another user.
[0034] In one implementation, Block S120 applies a level estimator
and/or other processing algorithm to determine a type of sound in
the audio signal, as shown in FIG. 2. For example, Block S120 can
determine the audio signal to include music, speech, or machine
noise. In one example implementation, Block S120 evaluates the
audio signal to identify a key characteristic of the audio signal,
such as volume, type of sound (e.g., speech, music, white noise),
proximity or origin of sound, and/or any other factor that informs
selection of a processing algorithm to apply to the audio signal to
augment the user's consumption of the audio signal. For example,
Block S120 can apply a Weighted Overlap-Add (WOLA) filter bank to
decompose the audio signal into discrete frequency bands, wherein a
substantially continuous tone or set of tones without substantial
variation in tonal quality or amplitude is associated with machine
noise, wherein interrupted tones in the range of 300 Hz to 3400 Hz
is identified as speech, and wherein continuous sound of varying
amplitude across a varying range of frequencies is identified as
music. In this example, Block S120 can qualify the audio signal to
greater resolution, such as by identifying machine noise
originating specifically from a computer cooling fan or from a car
engine.
[0035] In another example, Block S120 can identify a man's voice, a
woman's voice, a child's voice, and/or the user's voice in the
audio signal and, based on fluctuations in and/or reverberations of
an identified voice, characterize the voice as speaking,
whispering, shouting, singing, and/or humming, etc. Then, in this
example, Block S120 can qualify the audio signal containing the
voice(s) as local conversation, a phone call, music, or ambient
noise, etc. Block S120 can further qualify the audio signal based
on timing of one voice in the audio signal relative to another
voice in the audio signal. For example, if Block S120 identifies
two separate voices of similar audible level and that occur
substantially asynchronously in the audio signal, Block S120 can
characterize the audio signal as a live phone call between the user
and another individual, and, if Block S120 identifies two separate
voices at significantly different audible levels occurring
substantially asynchronously in the audio signal, Block S120 can
characterize the audio signal as a live local conversation between
the user and another individual.
[0036] Block S120 can additionally or alternatively estimate the
origin of a particular sound in the audio signal. Based on origins
of sounds in the audio signal, Block S120 can assign priority
levels to one or more sources of the sound in the audio signal. In
the implementation in which Block S110 collects the audio signal
from a single microphone, Block S120 can analyze the audio signal,
identify echoes in the audio signal, and generate a sound map of
the space occupied by the user based on the identified echoes in
the audio signal. Similarly, in the implementation in which Block
S110 collects audio signals from multiple microphones, Block S120
can combine the multiple audio signals into a three-dimensional
sound image of the space occupied by the user. Block S120 can also
analyze volume, frequency, and/or frequency-response data of the
space occupied by the microphone (e.g., the mobile computing device
and/or the audio device) to identify sounds originating near the
microphone (and therefore near the user) and sounds originating
substantially removed from the microphone (and therefore removed
from the user). In an example in which the user is in a crowded
restaurant, Block S120 can apply a highest priority to sounds
originating nearest and in front of the user, a moderate priority
to sounds originating nearest and behind the user, and a lowest
priority to sounds originating at a distance greater than eight
feet from the user. Similarly, in an example in which the user is
in an auditorium, Block S120 can apply a highest priority to sounds
originating furthest and in front of the user, a moderate priority
to sounds originating nearest and beside the user, and a lowest
priority to sounds originating behind the user. In these examples,
Block S130 can select or adjust a sound profile according to
priorities set by Block S120, and Block S140 can apply a filter to
the audio signal according to priorities set in Block S120.
However, Block S120 can estimate and apply sound origin data in any
other suitable way.
[0037] Block S120 can also implement voice detection, voice
recognition, and/or other audio processing techniques to identify
the voice in the audio signal. For example, Block S120 can assign
priority to a voice that is determined to be particularly relevant
to the user, such as a coworker who often speaks with the user, a
person at a dining table with the user, or a speaker in an
auditorium. In this example, the method S100 can filter out sounds
and/or voices not prioritized in Block S120 such that the user can
hear and focus on sounds most relevant to him. In another example,
Block S120 can recognize and flag the user's voice. In this
example, the method S100 can further filter out the user's voice,
thus aiding the user in audibly discerning other sounds while
talking, singing, etc. without substantially amplifying his own
voice. Block S120 can further detect changes in the audio signal to
trigger changes to sound profile, such as in response to a switch
from detected speech to detected music or song in the audio
signal.
[0038] Block S120 can additionally or alternatively quantify the
volume of the audio signal, such as by extracting the amplitude
(i.e., volume) of components of the audio signal. From these data,
Block S140 can remove or filter out--from the audio signal--sounds
below a threshold volume level. For example, Block S140 can filter
out a low hum of a refrigerator or low-volume cyclic insect sound.
In another example, Block S140 can filter out or attenuate sounds
above a threshold volume, such as to implement hearing protection
functionality.
[0039] Block S120 can additionally or alternatively qualify the
audio signal as a particular audio type based on a source of the
audio signal. For example, when implemented within a native hearing
augmentation application executing on the user's mobile computing
device, for Block S120 can qualify the audio signal as a speech in
a phone call when a native phone application is active on the
mobile computing device, as music when a native music playback
application is active on the mobile computing device, and as an
audio component of a video when a native video application is
active on the mobile computing device. In this example, Block S120
can also analyze a filename for a music track or video in playback
on the mobile computing device to identify a type of music
represented in the track (e.g., rock, punk, classical, reggae, or
R&B, etc.) or a type of audio represented in the video (e.g.,
music, speech, action noise, ambient noise, machine noise, etc.),
respectively. Block S120 can also filter available audio types
(from the set of audio types) based on a source of the audio
signal. For example, when implemented on a peripheral device
arranged between the user's mobile computing device and the
connected audio device, Block S120 can filter the set of audio
types in the set down to live audio for audio signal received from
a microphone within the peripheral device and the connected audio
device (e.g., a setoff headphones) and prioritize prerecorded audio
signal classification for audio signals received from the mobile
computing device.
[0040] However, Block S120 can function in any other way to assign
an audio type to an audio signal received or captured in Block
S110.
4. Sound Profile
[0041] As shown in FIG. 1, Block S130 of the method S100 recites
selecting, from a set of sound profiles, a particular sound profile
corresponding to the particular audio type. Generally, Block S130
functions to select a sound profile specific to the audio type,
which is subsequently implemented in Block S140 in conjunction with
the user's hearing profile to modify the audio signal in
anticipation of the user's particular hearing needs for the
particular audio type. For example, Block S130 can retrieve the
particular sound profile from a set of sound profiles stored
locally on the user's mobile computing device or on the peripheral
device based on an the audio type identified in Block S120.
Alternatively, Block S130 can download the sound profile from a
remote server and locally store the sound profile independently or
with a limited set of common-use sound profiles on the user's
mobile computing device or on the peripheral device.
[0042] In one implementation, sound profiles in the set of sound
profiles are static or `fixed` across all users over time.
Alternatively, when a new account is created for new user, a
standardized sound profile (i.e., common across multiple new users)
can be assigned to the user, and the sound profile can be
subsequently modified for the user--independent adjustments to the
same standard sound profile for other users--over time as the user
supplies feedback during application of the sound profile to
various audio signals. For example, in one variation of the method,
Block S130 detect an audio type of a sound output from the audio
device, receives an audio output adjustment from the user,
generates a sound profile for the audio type based on the audio
output adjustment from the user, and stores the sound profile with
the set of sound profiles. For example, in this variation, Block
S130 can adjust a volume setting, an equalizer (EQ) setting, and/or
another user preference within the sound profile for a particular
audio type as the user makes adjustments to a processed audio
signal of an identified type over time. Additionally or
alternatively, Block S130 can populate the set of audio profiles by
generating new audio profiles based on user audio adjustments made
during identified use scenarios classified as new or more-specific
audio types. For example, Block S130 can detect an ambient noise
condition, receive a volume adjustment from the user during output
of a sound from the audio device, and then generate a sound profile
for a new audio type associated with the ambient noise condition
based on the volume adjustment entered by the user. Block S120 can
subsequently match an audio signal to the ambient noise condition,
and Block S130 can retrieve the sound profile for the ambient noise
condition accordingly.
[0043] Yet alternatively, Block S130 can select from the set of
sound profiles that is populated over time from adjustments made by
various users during various classified scenarios, and the sound
profiles in the set can also be updates or modified over time based
on adjustments made across various users. For example, Block S130
can generate and/or update sound profiles based on feedback from
users of various demographics (e.g., age, gender, ethnicity,
occupation, location, etc.) and then group feedback and
corresponding updated sound profiles accordingly. In this example,
Block S130 can thus select a particular sound profile--from the set
of sound profiles--that is associated or `tagged` with one or more
demographics shared with the user.
[0044] Thus, as shown in FIG. 2, Block S130 can access one or more
demographics of the user and apply the demographic(s) of the user
to selection of the particular sound profile from the set. For
example, Block S130 can extract an age, gender, location,
ethnicity, and/or occupation of the user from a user profile stored
within a social networking system linked to the native hearing
augmentation application executing on the user's mobile computing
device. Block S130 can subsequently select a particular sound
profile previously elected by a second user of a demographic (e.g.,
an age, a gender, etc.) similar to one or more demographics of the
user. Additionally or alternatively, Block S130 can identify a
location of the user, such as by retrieving a current location of
the user's mobile computing device from a Global Positioning System
(GPS) sensor within the mobile computing device. In this
implementation, Block S130 can subsequently select a particular
sound profile--from the set of sound profiles--that corresponds to
the particular audio type for a location type including the
location of the user or that falls within a threshold range or
distance of a particular location associated with the particular
sound type.
[0045] In one implementation, Block S130 selects an sound profile,
to be applied to the audio signal in Block S140, from a database of
algorithms (e.g., filters) unique to the user. In this
implementation, the database of algorithms includes preset sound
profiles selected, preferred, and/or developed by the user over
time in conjunction with a native application, applet, or other
software module, such as executing on the user's mobile computing
device. The database of algorithms can therefore include an sound
profile tailored by and/or specific to the user for one or more use
scenarios. In another implementation, Block S130 selects the sound
profile--to be applied to the audio signal in Block S140--from a
database of algorithms shared across a set of users including the
user. In this implementation, algorithms in the database can be
static and preset, or the algorithms can be added and/or adjusted
by one or more users in the set of users over time, such as to
crowdsource creation and refinement of sound profile, such as for a
particular user demographic, a particular hearing or sound
preference, a particular location, a particular user habit, etc.
Therefore, in this implementation, the user can be grouped with a
set of users according to similar hearing or sound preferences,
similar demographic(s), similar locations, similar habits, etc.
However, Block S130 can select sound profile from any other one or
more databases of algorithms in any other suitable way.
[0046] Additionally or alternatively, Block S130 can adjust a
current or selected sound profile. For example, Block S130 can
adjust a channel transformation of a current filter or gain applied
to a particular channel to account for real-time changes in
sound-related parameters. For example, for a selected sound profile
particular to a certain restaurant, Block S130 can adjust a
transformation specified by the sound profile as the restaurant
becomes more crowded (and therefore more boisterous) and/or as the
restaurant becomes less crowded (and therefore quieter). In another
example, for a selected sound profile particular to the user's
habitual weeknight reading, Block S130 can adjust a transformation
specified by the sound profile to specify an overall decrease in
total sound level as the user's typical bed time approaches.
However, Block S130 can function in any other way to select and/or
adjust the sound profile.
[0047] Block S130 can therefore select and/or adjust the sound
profile dynamically according to any one or more of the user's
hearing profile, the user's location, the user's demographic, a
quality of audio-based hardware of one or more devices implementing
the method S100 (e.g., the user's mobile computing device, the
peripheral device, and/or the audio device), a vital quality of one
or more devices implementing the method S100 (e.g., remaining
battery life in the mobile computing device), a current time of
day, and/or a detected user action, etc.
[0048] As shown in FIG. 3, Block S130 can implement the user's
hearing profile (as described in U.S. Provisional Application No.
61/880,367, filed on 20 Sep. 2013 and incorporated herein by
reference) to access quantitative and/or qualitative data
pertaining to how well the users hears certain frequencies. Block
S130 can also access hearing preferences of the user from the
hearing profile, such as sensitivity to high frequency sounds.
Based on the hearing profile, Block S130 can select and/or adjust
the sound profile to complement the user's hearing needs and/or
hearing preferences. For example, the hearing profile can indicate
that the user has difficulty hearing sounds between 20 Hz and 120
Hz, which Block S130 can implement by selecting (or adjusting) the
sound profile that increases the gain in the audio signal within
the range of 20 Hz and 120 Hz. In another example, the hearing
profile can indicate that the user prefers not to hear
low-frequency machine noise while working but does prefer
low-frequency machine noise (e.g., as white noise) while sleeping,
and Block S130 can implement these preferences by selecting (or
adjusting) a first sound profile that attenuates machine noise
during the day and by selecting (or adjusting) a second sound
profile that boosts machine noise at night.
[0049] As shown in FIG. 3, Block S130 can implement the user's
location to select an sound profile particular to a certain
setting, room, or space or to a certain type of setting, room, or
space. In one implementation, Block S130 accesses GPS data, Wi-Fi
data, cellular data, a user check-in, or recent user credit card
data, etc. to determine or estimate the current location of the
user. From these data, Block S130 can determine that the user is
currently occupying a particular room or a particular space. In
another implementation, Block S130 accesses data (e.g., GPS data
and/or motion data from cellular phones carried by the other users)
from other users proximal the user and estimates the type of space
currently occupied by the user. For example, Block S130 can
determine the user to be in a restaurant based on GPS data from
other users that shows clusters of two to six users in the space,
and Block S130 can further determine the crowdedness of the
restaurant based on the density of other users in the space.
[0050] Based on the location of or the determined or estimated
space occupied by the user, Block S130 can select (or adjust) the
sound profile based on a sound response of the space. The sound
response of the space can be estimated based on the size, shape,
type, and/or occupancy, etc. of the space, or selected from a known
sound response previously associated with the space. For example,
the sound response of a workspace of the user can attenuate high
frequency sounds and amplify low frequency sounds with minimal
echo. Block S130 can thus identify the sound response of the space
from a list of sound responses of spaces common to the user and
select the sound profile accordingly. Block S130 can additionally
or alternatively identify the sound response of the space from a
database of sound responses generated by and shared across multiple
users who frequent spaces common to the user. Block S130 can
therefore implement machine learning and/or crowd-sourcing
techniques to develop a sound response database of spaces or types
of spaces.
[0051] Block S130 can also generate a sound profile of the space
occupied by the user. For example, when the user enters the space,
Block S130 can trigger multiple sequential audible clicks from a
speaker within a smartphone carried by the user, record subsequent
reverberation of the clicks through the space, and characterize the
space according to the recorded reverberations, which can be
correlated with sound travel and dissipation through the space and
thus the size of, shape of, and/or materials within the space.
Block S130 can then access the foregoing sound response when the
user next enters the space. However, Block S130 can estimate how
the room responds to sound in any other suitable way.
[0052] Once the location, space, and/or sound response of the room
is identified, Block S130 can tailor the sound profile to the
user's hearing needs and/or to preferences specified in the user's
hearing profile.
[0053] As described above, Block S130 can also implement a
demographic of the user to predict a hearing preference of the user
and to then select or adjust the sound profile accordingly. In this
implementation, Block S130 can access any one or more of the user's
age, gender, marital or familial status, employment status,
cultural background or ethnicity, etc. and estimate a hearing
preference of the user based on preferences of other users of
similar demographics. For example, Block S130 can interface with an
online social network to automatically source user demographic
data, as shown in FIG. 1. In one implementation, the user's hearing
preference is applicable to one or more particular social settings
or during some form of identifiable human interaction. For example,
for the user who is over the age of fifty, Block S130 can
determine, based on the user's age, that the user is likely to
prefer amplification of sounds directly in front of him and
attenuation of sounds behind him, and for the user who is under the
age of thirty-five, Block S130 can determine, based on the user's
age, that the user is likely to prefer balanced amplification of
sounds around him. Similarly, for the user who lives alone or with
only a spouse, Block S130 can determine, based on the living
arrangement, that the user is likely to prefer amplification of
sounds directly in front of him and attenuation of sounds behind
him, and for the user who has a large family or lives with several
people, Block S130 can determine, based on the living arrangement,
that the user is likely to prefer balanced amplification of sounds
around him. Alternatively, the hearing preference can be entered
directly by the user, and Block S130 can select and/or adjust the
sound profile according to the determined or entered user
preference. However, Block S130 can apply the user's hearing
preference in any other way.
[0054] As shown in FIG. 3, Block S130 can additionally or
alternatively identify a particular person or persons with whom the
user commonly interacts. In this implementation, Block S130 can
apply priority to sounds, in the audio signal, associated with such
person or persons. For example, Block S130 can interface with the
online social network to identity a spouse, a parent, or a child of
the user. In this example, Block S130 can identify the presence of
the spouse, parent, or child proximal the user based on a mobile
phone number sourced from the online social network and a GPS
coordinate of a mobile phone associated with the mobile phone
number. Block S130 can thus select and/or modify the sound profile
accordingly, such as by selectively augmenting and/or prioritizing
a voice of one or more the spouse, parent, and/or child when each
is determined to be proximal the user.
[0055] As shown in FIG. 3, Block S130 can further leverage a second
sound profile implemented by a second user proximal the user. For
example, Block S130 can elect a second sound profile currently
implemented for the second user as a baseline to select or adjust
the sound profile for the user. The method S100 can also add
components (e.g., frequencies) of the second audio signal from the
second user to the audio signal, thereby augmenting the audio
signal with audio data from a second source. For example, if the
second user is seated in a prime listening location in a symphony
hall and the user is seated in a back corner of the symphony hall
(i.e., a less-than-optimal acoustic position), the method S100 can
boost (or replace) the audio signal of the user with a second audio
signal collected at a computing device and/or audio device arranged
on or carried by the second user, thereby augmenting the user's
listening experience with sound data from another user elsewhere in
the audience substantially in real-time. In another example, for
the second member who is seated near a third member at a conference
table, wherein the user is substantially removed from the second
and third members at the conference table, the method S100 can
augment an audio signal collected at the user's computing device
with a second audio signal and/or a third audio signal collected at
computing devices at the second member and the third member,
respectively, as each speaks, thereby enabling the user to hear the
second and third members.
[0056] As shown in FIG. 3, Block S130 can also implement a current
time and/or a current user action to select and/or adjust the sound
profile. In one implementation, Block S130 tracks the user's habits
over time and generate a schedule for the user accordingly. For
example, Block S130 can determines that the user often (e.g., with
at least 85% accuracy) is asleep between the hours of midnight and
6 am, wakes between 6:30 and 6:45 am, eats breakfast with his
roommate between 7:15 am and 7:30 am, commutes to work between 7:45
am and 8:30 am, works from 8:30 am until noon, etc. In this
example, Block S130 can adjust the sound profile to attenuate high
frequency noises between midnight and 6 am, boost-mid range noise
between 6:30 and 6:45 am (so the user does not miss his alarm
clock), amplify audible frequencies characteristic of the speech
(or more specifically the roommate's voice) between 7:15 am and
7:30 am, attenuate low-frequency noise (e.g., road noise) between
7:45 am and 8:30 am, attenuate high-frequency noise between 8:30 am
and noon while the user is at work, etc. Block can estimate a
current action of the user based on time according to a schedule
entered by the user, schedules common to the user's demographic,
the roommate's schedule, a coworker's schedule, etc.
[0057] As shown in FIG. 3, Block S130 can additionally or
alternatively estimate a current user action (and adjust the sound
profile accordingly) based on motion data of the user, such as
measured by an accelerometer and/or gyroscope incorporated into a
mobile computing device (e.g., smartphone) carried by the user and
implementing portions of the method S100. Block S130 can further
apply local sound data and/or location data of the user to verify
or further inform a current user action. In one example, Block S130
associates low detected user movement (e.g., below a threshold
displacement within a period of time) and low sound levels around 8
pm with reading, and Block S130 can thus adjust the sound profile
to attenuate substantially all sound at this time. In another
example, Block S130 can associate little movement and lots of sound
around 8 pm with watching television, and Block S130 can thus
adjust the sound profile to amplify frequencies that the user does
not hear well. In a further example, Block S130 can associate
little movement and little sound around loam with working, and
Block S130 can thus adjust the sound profile to attenuate
higher-frequency sounds. In yet another example, Block S130 can
associate lots of movement and a moderate sound level around 6 pm
with working, and Block S130 can thus adjust the sound profile to
attenuate frequencies associated with voices of (the user's)
children.
[0058] Block S130 can also account for a sound or signal input
profile of one or more microphones or amplifiers that record the
audio signal, as well as a sound or signal output profile for
amplifiers, speakers, and/or one or more devices implementing
portions of the method S100. In this implementation, Block S130 can
select and/or tailor the sound profile to account for how sound is
altered when recorded and output to the user through various
devices such that a particular quality of a particular sound type
is heard by the user across various devices or combinations of
devices.
[0059] Block S130 can further select and/or adjust the sound
profile based on a vital of the computing device implementing a
portion of the method S100. In one implementation, Block S130
accesses a battery level of the computing device and selects and/or
adjusts the sound profile that extends the life of the device's
battery if the battery level is below a predetermined threshold.
For example, if the battery level is substantially low, Block S130
can select and/or adjust the sound profile that reduces processing
power and/or audio power by selectively augment sound to give user
only what is most necessary for the user to function.
[0060] By applying one or more of the foregoing techniques, Block
S130 can select and/or adjust the sound profile that is
particularly suitable for application to the audio signal for the
user at a particular (i.e., current) time. For example, the sound
profile can therefore be tailored and/or specific to music through
headphones, watching a concert in a particular venue, talking on
the phone with a phone to the ear in a crowded space, talking on
the phone via speakerphone in a quiet room, conversing with friends
at a table in a restaurant, working at a desk in a quiet office,
hiking up a mountain, watching television at home, watching a
sporting event in a bar, during band practice, while driving, or in
any other scenario or setting classified in Block S120. Block S130
can also adjust multiple sound profiles simultaneously and thus
enable the user to elect or switch between sound profiles manually
and substantially on the fly.
[0061] Block S130 can repeat continuously or cyclically (e.g., at a
specified time interval) to adjust the sound profile substantially
in real-time. For example, Block S130 can cycle at a rate of 10 Hz
to continuously detect the user's current action, location, etc.
and to update the sound profile accordingly, such as as the user
moves between rooms within a building or as a restaurant fills and
then empties over time. However, Block S130 can function in any
other way to select and/or adjust the sound profile that is applied
to the audio signal in Block S140.
5. Audio Signal Transformation
[0062] As shown in FIG. 1, Block S140 of the method S100 recites,
at the mobile computing device, transforming the audio signal into
a processed audio signal according to the particular sound profile
and the hearing profile of the user, as shown in FIGS. 1, 2, and 3.
Generally, Block S140 functions to apply the sound profile an the
user's hearing profile to the audio signal, thereby modifying the
audio signal to accommodate both the user's hearing ability (as
defined in the user's hearing profile) and the user's current audio
scenario (as defined by the selected sound profile). In particular,
Block S140 can attenuate, amplify, and/or leave unchanged one or
more channels (i.e., frequency bands) of the audio signal according
to the combination of the hearing profiles and the selected sound
profile. Block S140 can thus process the audio signal according to
the hearing profile and the sound profile to darken, brighten,
warm, or cool the audio signal, to target amplification of a
certain voice or group of voices in the audio signal, to balance
the audio signal for a certain frequency response of a room,
auditorium, or other space occupied by the user, or to boost or
augment the audio signal with audio data from a third party (e.g.,
second user), etc. In one example, Block S140 applies--to the to
the audio signal--a first equalizer setting specified by the
particular sound profile and a second equalizer setting specified
by the user's hearing profile. In this example, Block S140 can also
apply different weights to the hearing profile and the sound
profile in processing the audio signal. Alternatively, the sound
profile can define an algorithm for modifying the hearing profile
(or vice versa), and Block S140 can apply the sound profile to the
hearing profile to adjust the hearing profile for the classified
audio type of the audio signal before processing the audio signal
according to the adjusted hearing profile. In another example,
during a phone call hosted by the user's mobile computing device,
Block S140 attenuates a portion of a first audio signal
corresponding to a voice of the user and recorded at the user's
mobile computing device, amplifies a portion of a second audio
signal received from another device (of another user) according to
the particular sound profile, and combines the processed first
audio signal with the processed second audio signal. In yet another
example, a transformation of the audio signal specified in a sound
profile can define compression and/or gain parameters for one or
more frequencies within the audio signal, and Block S140 can
decompose the audio signal into various frequency bands (i.e.,
frequency channels) and apply a particular transformation specified
in the sound profile to each corresponding frequency band.
[0063] In one implementation, Block S140 also retrieves the user's
hearing profile for subsequent application to the audio signal. For
example, Block S140 can collect an identifier of the user's mobile
computing device, the peripheral device, and/or the connected audio
device and then retrieve the hearing profile from the user's
hearing account (stored in a remote database or locally on the
mobile computing device or on the peripheral device) by matching
identifiers tagged to the hearing profile to the identifiers
collected from the mobile computing device, the peripheral device,
and/or the connected audio device. Block S140 can thus select a
user hearing profile--from a set of available user hearing
profiles--specific to a current combination of mobile computing
device, peripheral device, and/or connected audio engaged by the
user.
[0064] In one implementation, Block S140 aggregates the user's
hearing profile, the sound profile, and local and/or environmental
conditions into a composite output profile and processes the audio
signal according to the composite output profile. In this
implementation, the method S100 can dynamically adjust the
composite output profile according to a changing audio signal
and/or a changing local or environmental condition based on
feedback and use data supplied by other users. In particular, Block
S140 can dynamically modify a transformation of one or more
frequencies within the sound signal as defined by one or both of
the hearing profile and the sound profile. For example, Block S140
can select, set, and/or adjust parameters of a sound and/or hearing
profile applied to the audio signal dynamically and over time based
on a change in user location, ambient noise level, detected audio
type, etc. detected in Block S130.
[0065] In the foregoing implementation, Block S130 can collect
environmental data from various users over time, store these data
in a database, identify changes in environmental conditions within
the data, and pair or `tag` identified environmental changes with
user feedback. In one example, Block S130 identifies an increase in
ambient noise in a datum collected from a first user and tags this
datum with a manual increase in volume of output audio entered by
the first user. In another example, Block S130 collects a local
sound response through a microphone within a smartphone associated
with a second user, identifies a change in the local sound response
(e.g., as a user walks into a different room or as a room occupied
by the second user fills with additional people), and tags the
change in local sound response with a corresponding manual EQ
setting change entered by the second user. Block S130 can thus
collect, analyze, and store such events and tag these events with
feedback from corresponding users. Block S140 can subsequently
modify the sound profile, the hearing profile, and/or the composite
output profile according to detected events and corresponding tags,
such as in real-time as new events are detected and matched to past
events paired with user feedback.
[0066] Block S140 can further implement the hearing and sound
profiles to enable various other functionalities, such as hearing
protection, or to aid a particular user action, such as talking on
the phone, driving a car, or conversing in a meeting. However,
Block S140 can function in any other way to process the audio
signal according to the selected sound profile.
6. Audio Output
[0067] As shown in FIG. 1, Block S150 of the method S100 recites
outputting the processed audio signal at the connected audio output
device. Block S150 functions to output an electrical (analog or
digital) signal that is converted into sound at a speaker within
the connected audio device. For example, Block S140 can generate
the processed audio signal locally on the user's mobile computing
device, and Block S150 can output the processed audio signal as an
analog signal through an audio jack integrated into the mobile
computing device and connected to the audio device (e.g., a set of
headphones), wherein a speaker within the audio device converts the
analog signal into sound for the user. In another example, Block
S140 can generate the processed audio signal remotely on a computer
network and then stream the processed audio signal to the user's
mobile computing device, such as over a Wi-Fi or cellular
connection, and Block S150 can wirelessly transmit the processed
audio signal as an digital signal to the audio device, such as over
Bluetooth, wherein a speaker within the audio device converts the
digital signal into sound for the user. In yet another example,
Blocks S106, S110, S120, S130, S140, and S150 execute on the
peripheral device connected to the user's mobile computing device
and to the audio device, wherein Block S110 receives the audio
signal over a wired (or wireless) connection to the mobile
computing device, Block S140 generates the processed audio signal
locally, and Block S150 outputs the processed audio signal over an
integrated audio jack connected to the audio device (e.g., a set of
headphones). Thus, Block S150 can substitute the audio signal for
the processed audio signal at an output to the audio device. In
particular, Block S150 can output the processed audio signal
substantially in real-time with the audio signal.
[0068] Block S150 can additionally or alternatively output and/or
transmit (e.g., wireless) the processed audio signal to a
standalone speaker, a home, car, or other stereo system, a headset,
an external mobile computing device (e.g., another user's phone),
and/or to any other audio output device in communication with the
user's mobile computing device, in communication with the
peripheral device, and/or with a vicinity of the user.
[0069] As shown in FIG. 4, one variation of the method S100 further
includes Block S160, which recites transcribing the audio signal
into a stream of text and displaying the stream of text on the
mobile computing device substantially in real-time within the audio
signal. Generally, Block S160 functions to implement audio-to-text
transcription methods or techniques to identify one or more words
or phrases in the audio signal and to make the one or more words or
phrases visually available to the user. Because context and meaning
can be more easily and more quickly comprehended when read as
opposed to heard, Block S160 can enable the user to identity the
context (and content) of speech captured in the audio signal
without necessitating replay of a past portion of the audio signal.
In one implementation, Block S160 transcribes all words identified
in speech captured in the audio signal and renders these words in
text format on a display of the user's computing device (e.g.,
smartphone) executing other Blocks of the method S100. In another
implementation, Block S160 filters identified words in the audio
signal down to keywords renders these keywords in text format on
the display, as shown in FIG. 4. In this implementation, Block S160
can enable the user to identify context of the speech by accessing
keywords, which may be more efficient, quicker, and/or easier for
the user to comprehend quickly than reading a substantially
complete transcription. However, Block S160 can function in any
other way to transcribe all or a portion of language in the audio
signal and to display the transcribed portion of the audio signal
on a display of the user's computing device.
7. Other Users
[0070] In one variation of the method S100, once a second user
completes a hearing test and a hearing profile is thus generated
for the second user as described above, the method S100 identifies
a change in an environmental condition proximal the second user,
such as by analyzing a microphone output, a GPS sensor output,
and/or an accelerometer output, etc. within a smartphone carried by
the second user. Thus, when a change in an environmental condition
proximal the user similar to a change in environmental condition
stored in the database is identified, Block S140 can automatically
apply a change to the particular sound profile, to the user's
hearing profile, and/or to the composite output profile to
anticipate a manual input by the user based on a detected change in
environmental condition similar to a detected change in an
environmental condition proximal the second user and tagged with
feedback from the second user. For example, if the method S100
identifies a change in local sound response proximal the second
user (e.g., by interfacing with a microphone within a smartphone
associated with the second user), Block S140 can apply this
feedback from the second user to the user by automatically
adjusting an EQ setting of the user's current composite output
profile to mimic the manual EQ setting change entered by the second
user. Block S140 can therefore respond to changing environmental
conditions proximal the user substantially in real-time by
automatically applying changes to the user's current hearing
profile, sound profile, or composite output profile based on
feedback from other users who previously experienced similar
changes in local environmental conditions.
[0071] In this variation, Block S140 can also apply
manually-entered audio output changes from other users to the
user's composite output profile based on a hearing profile of the
user and/or a demographic of the user. For example, Block S140 can
apply manually-entered audio output changes to the user's composite
output profile only for feedback entered by other users with
hearing abilities similar to that of the user (e.g., based on
similarities in the user's hearing test and hearing tests of other
users). In another example, Block S140 applies manually-entered
audio output changes to the user's composite output profile only
for feedback submitted by other users within the same age bracket
and of the same gender as the user.
[0072] Block S140 can implement similar techniques to apply
manually-entered audio output changes by other users to the user's
composite output profile based on a change in the user's location,
entry of the user into a different space of known location or sound
response, a change in proximity of the user to other users (e.g.,
based on GPS locations of smartphones associated with other users),
and/or a change in the user's activity (e.g., from working at a
desk to walking, from exercising to driving), etc. For example,
Block S130 can collect feedback from various users before, during,
and/or after such changes and store this feedback with
corresponding changes, and Block S140 can later apply this feedback
in the form of automatic (e.g., real-time) adjustment of the user's
composite output profile when similar changes of, by, or proximal
the user occur. However, Blocks of the method S100 can function in
any other way to dynamically modify the user's composite output
profile in response to a changing condition of or proximal the
user.
[0073] Additionally or alternatively, after the user completes a
first hearing test, Block S130 can collect user location data,
environmental data, and/or ambient (e.g., noise) conditions
proximal the user over time. The method S100 can further apply
these data to characterize common "noise conditions" proximal the
user (e.g., common sounds or noises recorded at the user's mobile
computing device), such as based on time of day, day of the week,
month, season, user location, etc. When the user completes a
subsequent hearing test, Block S104 and/or Block S140 can retrieve
feedback from other users associated with similar noise conditions
and then generate an updated hearing profile for the user based on
such feedback. The updated hearing profile can thus incorporate
conditional hearing profile elements that enable automatic (i.e.,
dynamic) adjustment of the composite output profile for the user
(e.g., without necessitating perpetual access to a remote database
containing changes in environmental conditions and associated
feedback tags from other users). For example, Block S104 can
generate the user's hearing profile that inherently incorporates
environmental changes and feedback from other users through "if . .
. then . . . " statements defined within the user's hearing
profile. Yet alternatively, Block S140 can update the user's
hearing profile over time, such as additional user location data,
environmental data, and/or ambient conditions proximal the user are
collected over time (rather than in response to completion of a new
hearing test by the user). However, the method S100 can function in
any other way to implement feedback from other users into the
user's hearing profile and/or into a composite output profile for
the user.
[0074] The systems and methods of the embodiments can be embodied
and/or implemented at least in part as a machine configured to
receive a computer-readable medium storing computer-readable
instructions. The instructions can be executed by
computer-executable components integrated with the application,
applet, host, server, network, website, communication service,
communication interface, hardware/firmware/software elements of a
user computer or mobile device, or any suitable combination
thereof. Other systems and methods of the embodiments can be
embodied and/or implemented at least in part as a machine
configured to receive a computer-readable medium storing
computer-readable instructions. The instructions can be executed by
computer-executable components integrated by computer-executable
components integrated with apparatuses and networks of the type
described above. The computer-readable medium can be stored on any
suitable computer readable media such as RAMs, ROMs, flash memory,
EEPROMs, optical devices (CD or DVD), hard drives, floppy drives,
or any suitable device. The computer-executable component can be a
processor, though any suitable dedicated hardware device can
(alternatively or additionally) execute the instructions.
[0075] As a person skilled in the art will recognize from the
previous detailed description and from the figures and claims,
modifications and changes can be made to the embodiments of the
invention without departing from the scope of this invention as
defined in the following claims.
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