U.S. patent application number 16/445908 was filed with the patent office on 2019-10-03 for adaptive nullforming for selective audio pick-up.
This patent application is currently assigned to Bose Corporation. The applicant listed for this patent is Bose Corporation. Invention is credited to Alaganandan Ganeshkumar, Jeremy Kemmerer.
Application Number | 20190304427 16/445908 |
Document ID | / |
Family ID | 64332190 |
Filed Date | 2019-10-03 |
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United States Patent
Application |
20190304427 |
Kind Code |
A1 |
Kemmerer; Jeremy ; et
al. |
October 3, 2019 |
ADAPTIVE NULLFORMING FOR SELECTIVE AUDIO PICK-UP
Abstract
Audio pickup systems and methods are provided to enhance an
audio signal by removing noise components related to an acoustic
environment. The systems and methods receive a primary signal and a
reference signal. The reference signal is adaptively filtered and
subtracted from the primary signal to minimize an energy content of
a resulting output signal.
Inventors: |
Kemmerer; Jeremy;
(Holliston, MA) ; Ganeshkumar; Alaganandan; (North
Attleboro, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Bose Corporation |
Framingham |
MA |
US |
|
|
Assignee: |
Bose Corporation
Framingham
MA
|
Family ID: |
64332190 |
Appl. No.: |
16/445908 |
Filed: |
June 19, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
15800909 |
Nov 1, 2017 |
10354635 |
|
|
16445908 |
|
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G10L 2021/02161
20130101; G10L 2021/02165 20130101; G10K 11/16 20130101; G10L
2021/02082 20130101; G10L 2021/02166 20130101; G10L 21/0208
20130101; H04R 3/005 20130101; G10K 2210/3028 20130101; G10L 15/22
20130101 |
International
Class: |
G10K 11/16 20060101
G10K011/16; H04R 3/00 20060101 H04R003/00; G10L 21/0208 20060101
G10L021/0208 |
Claims
1. A method of enhancing an audio signal, the method comprising:
receiving a primary signal; receiving one or more reference signals
derived from one or more microphones; adaptively filtering each of
the one or more reference signals to provide one or more filtered
signals; providing a noise estimate signal as a combination of one
or more of the one or more filtered signals; subtracting the noise
estimate signal from the primary signal to provide an output
signal; and adapting the adaptive filtering of each of the one or
more reference signals to minimize an energy content of the output
signal, such that a signal component produced by a new acoustic
source is adapted by the adaptive filters, over time, to be
included in the noise estimate signal.
2. The method of claim 1 further comprising monitoring the output
signal for a desired signal, and stopping adapting the filtering of
each of the plurality of reference signals upon detecting the
desired signal.
3. The method of claim 2 wherein monitoring the output signal for a
desired signal includes monitoring the output signal for a wake-up
word.
4. The method of claim 1 further comprising providing the primary
signal from a primary microphone.
5. The method of claim 1 further comprising combining a plurality
of signals from a plurality of microphones to provide the primary
signal.
6. The method of claim 1 further comprising separating each of the
primary signal and each of the one or more reference signals into
sub-bands.
7. The method of claim 1 further comprising operating a background
adaptive filter upon each of the one or more reference signals, and
wherein adapting the filtering of each of the one or more reference
signals includes copying a set of filter weights from the
background adaptive filter.
8. An audio system, comprising: a primary input to receive a
primary signal; one or more reference inputs, each of the reference
inputs to receive a reference signal; one or more adaptive filters,
each of the adaptive filters configured to adaptively filter one of
the one or more reference signals to provide a filtered signal; and
one or more combiners configured to receive one or more of the
filtered signals and subtract the one or more of the filtered
signals from the primary signal to provide an output signal, each
of the one or more adaptive filters configured to adapt to a signal
component produced by a new acoustic source, over time, such that
the signal component is represented in the one or more filtered
signals, causing the output signal to be adapted toward a
substantially null response in the presence of the new acoustic
source.
9. The audio system of claim 8 further comprising a detector
configured to detect a desired signal content in the output signal
and to pause adaptation of the plurality of adaptive filters in
response to detecting the desired signal content.
10. The audio system of claim 9 wherein the detector is a wake-up
word detector.
11. The audio system of claim 8 further comprising a plurality of
microphones, at least one of the plurality of microphones
configured to provide at least one of the reference signals to at
least one of the one or more reference inputs.
12. The audio system of claim 11 further comprising a beamformer
configured to receive signals from one or more of the plurality of
microphones and to provide the primary signal to the primary
input.
13. A method of enhancing an audio signal, the method comprising:
receiving a plurality of audio signals derived from a plurality of
microphones; adaptively filtering at least one of the plurality of
audio signals to provide a noise estimate signal; combining the
noise estimate signal with at least one of the plurality of audio
signals to provide a resulting signal, wherein the adaptive
filtering adapts the noise estimate signal to minimize an energy
content of the resulting signal; monitoring the resulting signal
for a predetermined signal content; responsive to detecting the
predetermined signal content in the resulting signal, stopping the
adaptive filtering; and responsive to not detecting the
predetermined signal content in the resulting signal, continuing
the adaptive filtering such that, over time, energy of the
resulting signal is minimized.
14. The method of claim 13 further comprising providing the
resulting signal to an audio device.
15. The method of claim 13 wherein the predetermined signal content
is a wake-up word.
16. The method of claim 13 further comprising identifying one of
the plurality of audio signals as a primary signal, wherein
combining includes subtracting the noise estimate signal from the
primary signal.
17. The method of claim 16 wherein the primary signal is provided
by an array forming technique.
18. The method of claim 13 wherein stopping the adaptive filter
comprises reverting filter coefficients to prior values.
19. The method of claim 13 wherein adaptively filtering includes
operating a background filter and copying a set of filter
coefficients from the background filter at intervals.
20. The method of claim 19 wherein stopping the adaptive filtering
comprises not copying the set of filter coefficients from the
background filter at the next interval.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This patent application is a continuation of and claims the
benefit under 35 U.S.C. .sctn. 120 to U.S. patent application Ser.
No. 15/800,909 filed Nov. 1, 2017, titled ADAPTIVE NULLFORMING FOR
SELECTIVE AUDIO PICK-UP, published as U.S. Patent Application
Publication No. 2019/0130885, which is incorporated herein by
reference for all purposes.
BACKGROUND
[0002] Audio systems sometimes include one or more acoustic
transducers to convert acoustic signals into electrical signals
(e.g., microphones) to detect acoustics in the environment in which
they operate, and sometimes also include acoustic drivers (e.g.,
loudspeakers) to reproduce acoustic audio content from an
electrical signal. Microphones may be deployed in such systems for
the purpose of detecting desired audio, which may include a user's
speech for applications such as automatic speech recognition,
virtual personal assistants, and communications (e.g., telephone),
for example. Often, the environment in which the audio system is
used includes additional acoustic sources other than the desired
audio, such as televisions, other audio systems, noise from
equipment, etc., and these alternate acoustic sources may sometimes
interfere with the detection and/or processing of the desired
audio, e.g., the user's speech. The acoustic environment in which
the audio system operates may generally be unknown, and may change
significantly over time. Accordingly, alternate or undesired
acoustic signals may be unknown at the outset and may also change
significantly over time.
SUMMARY
[0003] Aspects and examples are directed to systems and methods to
pick-up desired audio signals, such as speech activity of a user,
and reduce other signal components, such as alternate acoustic
sources and/or background noise, to enhance the desired signal
components in an output signal. The systems and methods provide
enhanced isolation of the desired signal by removing or reducing
other signal sources. Various applications include automated speech
recognition for, e.g., virtual personal assistants (VPA), and the
like. Aspects and examples disclosed herein allow an audio system
to pick-up and enhance a desired signal, such as a user's voice, so
the user may use such applications with improved performance and/or
in noisy environments.
[0004] According to one aspect, a method of enhancing an audio
signal is provided and includes receiving a primary signal,
receiving a plurality of reference signals, each of the plurality
of reference signals from one of a plurality of reference
microphones, filtering each of the plurality of reference signals
to provide a plurality of filtered signals, combining the plurality
of filtered signals to provide a noise estimate signal, subtracting
the noise estimate signal from the primary signal to provide an
output signal, and adapting the filtering of each of the plurality
of reference signals to minimize an energy content of the output
signal.
[0005] Certain examples include monitoring the output signal for a
desired signal, and stopping adapting the filtering of each of the
plurality of reference signals upon detecting the desired signal.
Monitoring the output signal for a desired signal may include
monitoring the output signal for a wake-up word.
[0006] Some examples include providing the primary signal from a
primary microphone. Some examples include combining a plurality of
signals from a plurality of microphones to provide the primary
signal.
[0007] In certain examples, each of the primary signal and the
plurality of reference signals may be separated into sub-bands.
[0008] Some examples include operating a background adaptive filter
upon each of the plurality of reference signals, and wherein
adapting the filtering of each of the plurality of reference
signals includes copying a set of filter weights from the
background adaptive filter.
[0009] According to another aspect, an audio system is provided
that includes a primary input to receive a primary signal, a
plurality of reference inputs, each of the plurality of reference
inputs to receive a reference signal, a plurality of adaptive
filters, each of the plurality of adaptive filters configured to
adaptively filter one of the plurality of reference signals to
provide a filtered signal, and one or more combiners configured to
receive the plurality of filtered signals and subtract the
plurality of filtered signals from the primary signal to provide an
output signal.
[0010] Certain examples include a detector configured to detect a
desired signal component in the output signal and to pause
adaptation of the plurality of adaptive filters in response to
detecting the desired signal. In some examples, the detector is a
wake-up word detector.
[0011] Some examples include a plurality of microphones, at least
one of the plurality of microphones configured to provide at least
one of the reference signals to at least one of the plurality of
reference inputs. Certain examples also include a beamformer
configured to receive signals from one or more of the plurality of
microphones and to provide the primary signal to the primary
input.
[0012] In some examples, the plurality of adaptive filters are
configured to adapt to minimize an energy content of the output
signal.
[0013] In certain examples, each of the plurality of adaptive
filters includes an active filter and a respective background
adaptive filter, each active filter being configured to adapt by
copying filter weights from the respective background adaptive
filter.
[0014] According to another aspect, an audio system is provided and
includes a primary microphone to provide a primary signal, a
reference microphone to provide a reference signal, a filter
configured to receive the reference signal and provide a filtered
signal, the filter configured to apply a fixed filter response for
an interval and to update the fixed filter response upon the
expiration of the interval, a combiner to subtract the filtered
signal from the primary signal to provide an output signal.
[0015] In some examples, the interval is a fixed duration of
time.
[0016] Certain examples include a background adaptive filter
operating on the reference signal and the interval being based upon
a convergence time of the background adaptive filter, the
expiration of the interval being a time when the background
adaptive filter achieves convergence, and the update to the fixed
filter response being based upon a filter response of the
background adaptive filter at the expiration of the interval.
[0017] In certain examples detector is included and configured to
detect a desired signal in the output signal, and the interval
being based upon the detection of the desired signal.
[0018] Some examples include a second reference microphone to
provide a second reference signal, and a second filter configured
to receive the second reference signal and provide a second
filtered signal, the second filter configured to apply a second
fixed filter response for the interval and to update the second
fixed filter response upon the expiration of the interval, the
combiner configured to subtract the filtered signal and the second
filtered signal from the primary signal to provide the output
signal.
[0019] Certain examples may include a beamformer configured to
receive one or more microphone signals, including microphone signal
from the primary microphone, and to provide the primary signal as a
combination of the one or more microphone signals.
[0020] Still other aspects, examples, and advantages of these
exemplary aspects and examples are discussed in detail below.
Examples disclosed herein may be combined with other examples in
any manner consistent with at least one of the principles disclosed
herein, and references to "an example," "some examples," "an
alternate example," "various examples," "one example" or the like
are not necessarily mutually exclusive and are intended to indicate
that a particular feature, structure, or characteristic described
may be included in at least one example. The appearances of such
terms herein are not necessarily all referring to the same
example.
BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Various aspects of at least one example are discussed below
with reference to the accompanying figures, which are not intended
to be drawn to scale. The figures are included to provide
illustration and a further understanding of the various aspects and
examples, and are incorporated in and constitute a part of this
specification, but are not intended as a definition of the limits
of the inventions. In the figures, identical or nearly identical
components illustrated in various figures may be represented by a
like numeral. For purposes of clarity, not every component may be
labeled in every figure. In the figures:
[0022] FIGS. 1A-1C are schematic diagrams of an example environment
in which an example audio system may operate;
[0023] FIGS. 2A-2B are perspective views of various examples of an
audio system;
[0024] FIG. 3 is a schematic block diagram of an example audio
system;
[0025] FIG. 4 is a schematic block diagram of an example audio
system that includes an example of sub-band processing;
[0026] FIG. 5 is a schematic block diagram of an example audio
system that includes an example of background adaptation;
[0027] FIG. 6 is a schematic block diagram of an example audio
system that includes an example of activity detection;
[0028] FIG. 7 is a schematic block diagram of an example audio
system that includes an example of beamforming to provide a primary
signal;
DETAILED DESCRIPTION
[0029] Aspects of the present disclosure are directed to audio
systems and methods that pick-up a desired signal, such as a voice
signal of a user, while reducing or removing other signal
components not associated with the desired signal, e.g., the user's
speech. Providing a user's voice signal with reduced noise
components may enhance voice-based features or functions available
as part of an audio system or other associated equipment, such as
communications systems (cellular, radio, aviation), entertainment
systems (gaming), speech recognition applications (speech-to-text,
virtual personal assistants), and other systems and applications
that process audio, especially speech or voice. Examples disclosed
herein may be coupled to, or placed in connection with, other
systems, through wired or wireless means, or may be independent of
other systems or equipment.
[0030] The example audio systems and methods described herein may
include multiple microphones that provide one or more signals to
one or more adaptive filters to produce a substantially null
response to a particular acoustic environment. Operation of the
adaptive filters (and supportive signal processing) may cause the
audio system or method to adapt to the acoustic environment, on an
on-going basis, to substantially nullify the background acoustics.
In various examples, a substantially null response may include
providing an output signal with a minimized energy content. A
change in the acoustic environment, such as a user starting to
speak or the new presence of a desired signal, to which the
adaptive filters have not yet converged to nullify, may provide
components of the desired signal in an output signal. Conventional
methods that adapt to an acoustic environment to provide desired
signals require certain characteristics of the desired signal, such
as a certain source location or arriving phase relationship, and/or
require a blocking matrix to effectively enhance or cancel signals
from certain directions prior to adaptation, at the expense of
increased processing power, resources, and/or energy
consumption.
[0031] Production of a signal wherein a user's voice components are
enhanced while other components are reduced may be referred to
generally herein as voice pick-up, voice isolation, speech
enhancement, and the like. As used herein, the terms "voice,"
"speech," "talk," and variations thereof are used interchangeably
and without regard for whether such speech involves use of the
vocal folds.
[0032] Examples disclosed herein may be combined with other
examples in any manner consistent with at least one of the
principles disclosed herein, and references to "an example," "some
examples," "an alternate example," "various examples," "one
example" or the like are not necessarily mutually exclusive and are
intended to indicate that a particular feature, structure, or
characteristic described may be included in at least one example.
The appearances of such terms herein are not necessarily all
referring to the same example.
[0033] It is to be appreciated that examples of the methods and
apparatuses discussed herein are not limited in application to the
details of construction and the arrangement of components set forth
in the following description or illustrated in the accompanying
drawings. The methods and apparatuses are capable of implementation
in other examples and of being practiced or of being carried out in
various ways. Examples of specific implementations are provided
herein for illustrative purposes only and are not intended to be
limiting. Also, the phraseology and terminology used herein is for
the purpose of description and should not be regarded as limiting.
The use herein of "including," "comprising," "having,"
"containing," "involving," and variations thereof is meant to
encompass the items listed thereafter and equivalents thereof as
well as additional items. References to "or" may be construed as
inclusive so that any terms described using "or" may indicate any
of a single, more than one, and all of the described terms. Any
references to front and back, right and left, top and bottom, upper
and lower, and vertical and horizontal are intended for convenience
of description, not to limit the present systems and methods or
their components to any one positional or spatial orientation.
[0034] FIG. 1A illustrates an example environment 100 where an
example audio system 110 may be in use. The environment 100 may
include the audio system 110, a user 120 whose speech is to be
detected and provided for further processing, and one or more
additional acoustic source(s) 130, such as a television, a radio, a
fan, etc. When the user 120 speaks, he or she may produce a direct
acoustic signal 122 and/or one or more indirect acoustic signals
124, which may reach the audio system 110. An output signal
representative of the user's speech (e.g., representative of the
direct acoustic signal 122) is desired to be provided by the audio
system 110 for further processing, and may be in an electrical
(digital or analog) form, for example. The additional acoustic
source(s) 130 also may produce one or more direct acoustic signals
132 and/or indirect acoustic signals 134 that reach the audio
system 110. These acoustic signals from the additional acoustic
source(s) 130 are prefereably reduced or removed from being
represented in the output signal to be provided for processing.
Accordingly, an output signal provided by the audio system 110 may
include a robust signal-to-noise ratio (SNR), e.g., each of the
acoustic signals that are not the user's voice being considered
"noise" signals, for example.
[0035] Various examples described herein may apply adaptive filters
to one or more microphone signals to produce a substantially null
response to the acoustic environment (e.g., to acoustic signals in
the environment). For example, FIG. 1B illustrates the example
audio system 110 operating in the environment 100 while the user
120 is not speaking. A primary microphone associated with the audio
system 110 may pick up acoustic signals, such as the acoustic
signals 132, 134, arriving at the audio system 110, and provide a
microphone signal that includes components from many or all of the
acoustic sources in the environment. Additional microphones
(secondary or reference microphones) associated with the audio
system 110 may also pick up the same or similar acoustic signals,
e.g., forming an array of microphones providing individual
microphone signals having variations in arrival times, phase, and
amplitude, with respect to each other and the primary microphone.
Adaptive filters are applied in various examples to the reference
microphone signals and used to modify the primary microphone signal
to create a substantially null response, as described in more
detail below. Accordingly, a spatial response pattern 140 of the
audio system 110 may form null responses 142 for acoustic signals
arriving from the directions of, e.g., the acoustic signals 132,
134. While the spatial response pattern 140 may be shown as forming
beams and nulls, such is merely for illustrative purposes and
various examples described herein will not necessarily form beams
of enhanced response and will not necessarily form nulls in a
strict sense. Various examples may reduce an acoustic response for
acoustic signals coming from certain directions, e.g., based upon
the direction(s) to alternate acoustic sources and adaptation as
described herein, thus reducing representative content from such
acoustic sources in an output signal. Such reduced content and/or
reduced response may generally be referred to herein as
nullforming.
[0036] A change in the acoustic environment, such as a new acoustic
source or the user starting to speak, as illustrated in FIG. 1C,
may produce new acoustic signals, such as the acoustic signals 122,
124, for which the audio system 110 has not formed null responses
142. Accordingly, an output signal from the audio system 110 may
include components of the new acoustic signal, e.g., the user's
speech. In some examples, the adaptive filters operating on the
reference microphone signals may take some time to adapt to the new
acoustic signal (e.g., the speech of the user 120) and the time for
adaptation may be sufficient to detect that the user is speaking
and/or to detect what the user says (e.g., via speech
recognition).
[0037] In some examples, a time for adaptation by the adaptive
filters may be long enough for a command or instruction spoken by
the user 120 to be provided in an output signal, prior to the
adaptive filters forming a new null that may reduce or cancel the
user's speech. In some examples, a wake-up word spoken by the user
120 may be sufficiently short to be detected and trigger a freezing
of adaptation by the adaptive filters. In some examples, multiple
adaptive algorithms may operate in parallel upon each reference
microphone signal such that an adaptive filter operates with frozen
(or fixed) response (e.g., temporarily static filter
weights/coefficients) for at least some duration of time. In some
examples, adaptive filters acting upon reference microphone signals
may operate with a delay in updating their filter response (e.g., a
delay in updating a set of filter weights/coefficients), such that
new acoustic signals (such as the user 120 starting to speak)
provide components to the output signal during the time of the
delay. Accordingly, in various examples, an output signal provided
may include components of a user's speech that may be suitable for
further processing by, e.g., speech recognition, virtual personal
assistant, and other systems.
[0038] Each of FIGS. 2A and 2B illustrates an example audio system
110 having a primary microphone 210, a plurality of reference (or
secondary) microphones 220, and a controller 230 that includes
signal processing components/circuitry. In various examples, and as
shown, the primary microphone 210 may be a central microphone. In
other examples, a primary microphone may be any of the microphones
shown or another microphone. In yet other examples there may be no
particular primary microphone but there may be a primary signal
derived or formed from the signals from multiple microphones, e.g.,
such as in a beam-forming arrangement or other array processing.
The example audio systems 110 are shown having a particular form
factor, but any of various form factors may be accommodated.
Additionally, while FIG. 2A shows an example audio system 110
having four reference microphones and FIG. 2B shows an example
audio system 110 having six reference microphones, any number of
reference microphones, more or fewer than shown, may be suitable
and may be included in various examples. Placement and/or
arrangement of the various microphones 210, 220 may also be
different. Various examples of the systems and methods described
are insensitive to particular microphone placement. Further, some
examples may include additional primary microphones and/or other
microphones for various purposes.
[0039] While microphones are illustrated in the various figures and
labeled with reference numerals, such as reference numerals 210,
220, the visual element(s) illustrated in the figures may, in some
examples, represent an acoustic port wherein acoustic signals enter
to ultimately reach a microphone 210, 220, which may be internal
and not physically visible from the exterior. In examples, one or
more of the microphones 210, 220 may be immediately adjacent to the
interior of an acoustic port, or may be removed from an acoustic
port by a distance, and may include an acoustic waveguide between
an acoustic port and an associated microphone.
[0040] In some examples, the primary microphone 210 provides a
primary signal. In some examples, a primary signal may be provided
by combining signals from the microphones 210, 220, e.g., with
array processing, to maximize an acoustic response in a direction
from which the user is presumed to be speaking. In various
examples, adaptive filters operate upon a plurality of reference
signals (e.g., provided by the reference microphones 220) to
produce a nullifying signal which is used to modify the primary
signal to produce an output signal with a substantially null
response, e.g., when the user is not speaking. Accordingly, when
the user begins to speak the nullifying signal may fail to create a
substantially null response (e.g., at least for some period of
time) and the output signal may include components related to the
user's speech.
[0041] FIG. 3 illustrates at least one example of the audio system
110 that includes the primary microphone 210, reference microphones
220, and at least a portion of the controller 230 that includes
signal processing components/circuitry. The primary microphone 210
provides a primary signal 212, to include the user's voice when the
user speaks but which may also include components from additional
acoustic signals. Each of the reference microphones 220 provides a
reference signal 222 including substantially the same content as
the primary signal 212, but with differing arrival times, phases,
and/or amplitudes. In various examples, the reference signals 222
may be used as noise references to reduce or remove from the
primary signal 212 content associated with the acoustic environment
generally, e.g., while the user is not speaking, and therefore not
associated with the user's voice.
[0042] Each of the reference signals 222 may be processed through
an adaptive filter 232, whose outputs are combined by a combiner
234 to produce a noise estimate signal 224, which is subtracted
from the primary signal 212 by a combiner 236, to produce a voice
estimate signal 214, which may be provided as an output signal 240.
The adaptive filters 232 may include adaptive algorithms that
monitor the voice estimate signal 214 (e.g., shown as a feedback
signal 216) and may adapt the respective adaptive filter 232, e.g.,
at various intervals. The adaptive filter 232 may cause the noise
estimate signal 224 to improve at reducing content in the voice
estimate signal 214, particularly when the user 120 is not
speaking. Accordingly, when the user 120 is not speaking, the audio
system 110 converges to provide a nearly null output signal 240,
effectively reducing or nullifying the acoustic sources in the
environment from providing representative components to the output
signal 240. The adaptive filters 232, considered as a whole having
their individual signals combined to be subtracted from the primary
signal 212, may be deemed a multi-channel adaptive filter
system.
[0043] The adaptive filters 232 may include adaptive algorithms
that may be any number of adaptive algorithms known in the art, or
other adaptive algorithms. In some examples, the adaptive
algorithms may be any of a least mean square algorithm, a
normalized least mean square algorithm, a recursive least mean
square algorithm, or other algorithms, or may be a combination of
any of these or other algorithms.
[0044] In various examples, the adaptive filters 232 may be
configured to adapt during periods when the acoustic environment
includes only noise sources (e.g., not including the user's voice
or another desired signal) to determine appropriate filter
responses (e.g., adapted weights, coefficients) to substantially
reduce or remove noise content from the output signal 240, and to
apply the adapted weights or coefficients (e.g., maintain them in
operation in the filters 232) when a desired signal is present,
e.g, when the user speaks. In various examples, a time period may
provide a period of fixed or maintained filter weights or
coefficients, or a signal detection, such as a voice activity
detection (VAD), may trigger a freeze of adaptation to provide a
period of fixed or maintained filter weights, or a combination of
these or other approaches may be applied. For example, the adaptive
filters 232 may take some time to adapt to a changed acoustic
environment, such as the user beginning to speak, and such time may
be sufficient to provide the user's voice content in the output
signal. In other examples, additional or different time periods may
be applied by selecting adaptation parameters, e.g., step size or
adaptation constants, to produce relatively slow convergence and/or
alternate adaptive algorithms, such as switching between multiple
adaptive filters which adapt during disjoint time periods, for
example. In some examples, detection of a desired signal may
include voice activity detection, which may further include
detecting a wake-up word, e.g., during a time period before the
adaptive filters 232 adapt (and nullify) the changed acoustic
environment (e.g., the user beginning to speak).
[0045] Some examples may include only a single reference microphone
220 to provide a single reference signal, which may be adaptively
filtered by an adaptive filter 232, to provide substantial
nullification to an acoustic environment. A change in the acoustic
environment, such as a new desired signal, may provide components
of the desired signal in an output signal, as previously discussed,
even in such a single-channel (e.g., single reference microphone)
example. In various examples, components of the desired signal may
be included in the output signal while the adaptive filter(s)
adapts or converges to the new acoustic environment (which may
include a purposeful delay in convergence), and/or while the
adaptive filter(s) is frozen by operation of background adaptation
and/or signal activity detection or other mechanisms.
[0046] In some examples, the controller 230 may operate on various
microphone signals in sub-bands, such that each of the various
components of the controller 230 shown in FIG. 3 may include a
number of sub-components, each sub-component receiving and/or
operating upon only a particular sub-band portion of the various
signals described. For example, and with reference to FIG. 4, each
microphone 210, 220 may provide a signal to an optional sub-band
filter 410, which separates spectral components of each microphone
into multiple sub-bands, and an optional sub-band synthesizer 420
may re-combine the multiple sub-bands into a suitable output signal
240. Accordingly, for a system having "n" sub-bands, each of the
"m" adaptive filters 232 shown represents "n" adaptive filters, one
for each sub-band. Various examples may separate microphone signals
into 8, 16, 32, 64, 128 or more sub-bands. In certain examples, a
system having four (4) reference microphone channels (m=4)
processed across sixty-four (64) sub-bands (n=64) may include a
total of 256 (e.g., 4.times.64) adaptive filters 232, one per
sub-band per channel.
[0047] In some examples, signals from each microphone may be
processed in analog form but preferably are converted to digital
form by one or more ADC's, which may be associated with each
microphone, or associated with the sub-band filter 410, or
otherwise act on each microphone's output signal between the
microphone and the sub-band filter 410, or elsewhere, e.g., as part
of the controller 230. Accordingly, in certain examples the various
components act upon digital signals derived from each of the
microphones. Any of the ADC's, the sub-band filter 410, and other
components of the example audio systems 110 described herein may be
implemented, for example, by a digital signal processor (DSP)
configured and/or programmed to perform the various functions of,
or to act as, any of the components shown or discussed.
[0048] As discussed above, signals may be separated into sub-bands
by the sub-band filter 410 when received and re-combined by the
sub-band synthesizer 420 when provided at an output. Each of the
various components shown may therefore logically represent multiple
such components to process the multiple sub-bands. Further, the
sub-band filter 410 may process the microphone signals to provide
frequencies limited to a particular range, and within that range
may provide multiple sub-bands that in combination encompass the
full range. For example, the sub-band filter may provide sixty-four
(64) sub-bands covering 125 Hz each across a frequency range of 0
to 8,000 Hz. An analog to digital sampling rate may be selected for
the highest frequency of interest, for example a 16 kHz sampling
rate, to satisfy the Nyquist-Shannon sampling theorem, for example,
for a frequency range up to 8 kHz. Various examples may include a
narrower or broader frequency range and may include more or fewer
sub-bands, or may not include sub-band processing, in accord with
varying application and operational requirements. Sub-band
filtering, processing, and synthesis may be included in any of the
examples described herein without regard for whether such is
illustrated in any particular figure. In various examples, various
overlap add (OLA) or weighted overlap add (WOLA) methods with
varying configuration parameters (such as windowing, window size,
overlap length, etc.) may be implemented for sub-band filtering and
synthesis.
[0049] With continued reference to FIG. 4, the adaptive filters 232
may implement varying filter resolutions, or taps, across various
examples to accommodate varying operational requirements in
different environments. In various examples, the adaptive filters
232 may operate using 1 tap, 4 taps, 16 taps, 32 taps, or other
resolutions. In some examples, a filter resolution may be selected
in combination with a sub-band size, sampling rate, sampling bit
depth, and/or other processing parameters to achieve various
performance characteristic(s).
[0050] In various examples, a convergence time for the adaptive
filters 232 may be sufficient for a command or instruction spoken
by the user 120 to be provided in the output signal 240, prior to
the adaptive filters 232 forming a new null (e.g., minimizing an
energy response at the output signal) that may reduce or cancel the
user's speech. For example, some adaptive filters 232 may include a
convergence time of around 1 second. In other examples, a
convergence time of the adaptive filters may be purposefully
lengthened or delayed. For example, each of the adaptive filters
232 (with reference to FIGS. 3-4) includes a filter that filters a
respective signal from a reference microphone 220, and an adaptive
algorithm that updates, or adapts, the filter, as discussed above.
A slowed convergence of each of the adaptive filters 232 may, in
some examples, provide additional time for a command or instruction
spoken by the user 120 to be provided in the output signal 240. For
example, each of the adaptive algorithms associated with a
respective adaptive filter 232 may be tuned (e.g., by adjusting a
step size or other adaptation constant, for instance) or adjusted
to de-sensitize its response to changes in the acoustic
environment, thus slowing its convergence rate, e.g., lengthening a
time the adaptive filter 232 takes to adapt. Such a convergence
delay may be selected or designed to provide a convergence time of
3 seconds, 5 seconds, 8 seconds, or more in various examples.
[0051] In various examples, the adaptive filters 232 may include
multiple adaptive filters per microphone 220 (e.g., per channel)
(and in the case of sub-band processing, per sub-band) such that
each (sub-band) channel includes an active filter and a background
filter. The active and background adaptive filters may exchange
functions, from active to background and vice-versa, at intervals,
to create various intervals during which a desired signal, such as
a user's voice, may not be adapted, reduced, nulled, or canceled by
action of the adaptive filters 232. With reference to FIG. 5, a
schematic diagram of an example system 110 that includes active and
background adaptive filters is illustrated.
[0052] FIG. 5 shows an example audio system 110 in which signals
from each reference microphone 220 may be processed by an active
adaptive filter 232 and by a background adaptive filter 532. In
some examples, the background adaptive filter(s) 532 may
continuously adapt to minimize the response of an error signal 516,
while the active adaptive filter(s) 232 maintain a fixed (or
frozen) set of filter weights to provide a fixed response of an
output signal 240, at least for a period of time. At various time
intervals, such as a fixed interval of 3 seconds, 5 seconds, or 8
seconds or more in various examples, filter weights from the
background adaptive filter 532 may be copied to the active adaptive
filter 232. In some examples, the operation of the active and
background adaptive filters 232, 532 may be swapped, such that the
background adaptive filter 532 becomes active and frozen, and the
active adaptive filter 232 begins to adapt its filter weights as a
background adaptive filter.
[0053] In some examples, whenever the filter weights of an active
adaptive filter are changed (e.g., copied from the background
adaptive filter), the background adaptive filter may be re-set to
begin adaptation from a newly non-adapted state. In other examples,
the background adaptive filter may continue adaptation from the
previously adapted filter weights without re-setting.
[0054] In some examples, the active adaptive filters 232 may be
updated on the basis of criteria other than fixed intervals. For
example, the active adaptive filters 232 may be updated by, e.g.,
copying weights from the background adaptive filters 532, whenever
the background adaptive filters 532 have reached a particular level
of convergence. In certain examples, the background adaptive
filters 532 adapt from a re-set state and when the adaptation is
sufficiently complete, e.g., by the filter weights not changing, or
changing by less than a threshold and/or fractional amount, the
filter weights may be copied over to the active adaptive filters
232. In some examples, the background adaptive filters 532 may be
re-set after copying their weights to the active adaptive filters
232. In other examples, the background adaptive filters 532 may
continue to adapt and may copy their weights to the active adaptive
filters 232 at a later time, based upon, e.g., a threshold change
to the weights and/or a threshold convergence after such a change
to the weights. Accordingly, the active adaptive filters 232 may
operate with relatively fixed filter weights for various intervals,
the various intervals may be fixed intervals by design or may be
intervals based upon various criterion of the background adaptive
filters 532, such as a convergence criteria of the background
adaptive filters 532 and/or a threshold change having occurred in
the weights of the background adaptive filters 532. In each of
these example cases, a fixed response of the system may be
sufficiently long (e.g., in time) for a desired signal to be
provided and/or detected in the output signal 240.
[0055] In various examples, the various adaptive filters may be
frozen upon detection of the desired signal, such as when the user
is speaking, and accordingly may allow the desired signal to be
provided in the output signal 240 for a period of time following
such detection. For example, a voice activity detector may monitor
the estimated voice signal 214 and send a signal to the adaptive
filters 232 to pause adaptation upon detecting voice activity in
the voice estimate signal. In certain examples, a wake-up word may
be short enough in duration, relative to a convergence time of the
adaptive filters 232, to be detected in the output signal 240 and
signal the adaptive filters 232 to pause adaptation. Accordingly,
in some examples, a voice activity detector may be a wake-up word
detector.
[0056] With reference to FIG. 6, an example audio system 110 that
includes signal activity detection is illustrated. The adaptive
filters 232 may be controlled to pause adaptation while continuing
to filter signals based upon the most recent filter weights or
coefficients. The activity detector 602 may control when the
adaptive algorithms (associated with the adaptive filters 232) are
paused. For example, the activity detector 602 may monitor the
output signal 240 for an indication of a desired signal, such as a
particular spectral content, or the presence of a wake-up word, or
other criteria, and upon detecting the desired signal activity the
activity detector 602 may send a signal 604 to each of the adaptive
filters 232 to pause (or freeze) adaptation of its respective
filter weights or coefficients. In some examples, each of the
adaptive filters 232 may be configured to use filter weights or
coefficients that were calculated just prior to the desired signal
being detected. In various examples, the activity detector 602 may
generate the signal 604 to pause adaptation for a certain period of
time, such as 3 seconds, 5 seconds, 8 seconds, or more. In other
examples, the activity detector 602 may generate the signal 604
only while the desired signal continues to be detected. In other
examples, the adaptive algorithms may be configured to pause
adaptation for the certain period of time upon receiving the signal
604, or a period of time may be enforced in other ways.
[0057] In various examples, an activity detector, such as the
activity detector 602, may monitor other aspects of the audio
system 110 in addition to or instead of monitoring the output
signal 240. For example, an activity detector 602 may calculate a
correlation between the primary signal 212 and the noise estimate
signal 224 and may monitor the correlation for changes. A change in
the acoustic environment may cause the correlation between the
primary signal 212 and the noise estimate signal 224 to change,
thus the activity detector 602 may incorporate such a change in
correlation into a decision whether a desired signal is present.
Additionally, once converged, the weights applied by, e.g., the
adaptive filters 232 may remain substantially constant so long as
the acoustic environment remains unchanged. A change in the
acoustic environment, such as the presence of a desired signal,
e.g., a user speaking, causes the adaptive filters 232 to begin to
adjust the weights applied. Accordingly, a new or significant
change to the weights of the adaptive filters 232 may indicate a
change in acoustic environment, which may be related to a desired
signal. The activity detector 602 may incorporate such into a
decision whether a desired signal is present, and if so, pause
further adaptation and/or revert to filter weights in use just
before the change occurred.
[0058] In various examples, any of the elements particularly
described above with reference to FIGS. 3-6 may be combined for
advantageous effect. For example, delayed adaptation may provide a
slowed convergence time in which a desired signal (e.g., voice
activity, a wake-up word) may be detected, as illustrated in FIG.
6, to trigger a pause in adaptation. Further, active and background
adaptive filters as illustrated in FIG. 5 may be paused by a signal
from an activity detector as illustrated in FIG. 6. Further as
described above, sub-band filtering, processing, and synthesis may
be incorporated into any one or combinations of aspects illustrated
by FIGS. 3-6. Additionally, alternate systems and methods of
providing a primary signal may be combined with any of the aspects
of sub-band filtering, processing, synthesis, convergence times,
background adaptation, and activity detection. At least one example
of alternately providing a primary signal is described with
reference to FIG. 7
[0059] FIG. 7 illustrates an alternate example audio system 110
wherein the primary signal 212 is provided by action of a
beamformer 710. Any of the microphones 210, 220 may provide signals
to the beamformer 710 that may apply array processing to steer a
beam (e.g., a direction of enhanced acoustic response) toward an
expected location, e.g., of the user 120. In some examples,
multiple sets of beamforming weights (e.g., one set for each of
various directions) may be pre-configured (e.g., stored in memory),
and a selected set of the beamforming weights may be applied by the
beamformer 710. Operation of the adaptive filters 232 may be
independent of the method or system applied to provide the primary
signal 212, and therefore any of the above described operations of
the adaptive filters 232, sub-band processing, convergence times,
active and background adaptation, and activity detection, with
reference to FIGS. 3-7, may be advantageously applied to the
example audio system 110 of FIG. 7. Indeed, the example audio
system 110 illustrated in FIG. 7 may be a general case of the
example audio system 110 illustrated in FIG. 3, e.g., a beamformer
710 in FIG. 7 that selects and provides a signal from the primary
microphone 210 and rejects signals from the reference microphones
220 reduces to the specific case illustrated in FIG. 3.
[0060] Various examples of systems and methods in accord with those
described herein may include detection of various characteristics
of the noise field of the acoustic environment. For example,
adaptive systems and methods as described herein may exhibit more
robust performance in an acoustic environment having dominant
discrete acoustic noise sources and exhibiting high levels of
coherence between the various microphones. Systems and methods
described herein operating in a more diffuse acoustic field may
operate more robustly by including beamforming techniques such as
those described with reference to FIG. 7. Accordingly, some
examples detect whether a noise field of the acoustic environment
exhibits more discrete characteristics or more diffuse
characteristics, and may select various operating parameters based
in part upon the noise field detection. For example, use and
operation of beamforming to provide a primary signal,
aggressiveness of adaptive filters (e.g., convergence times),
and/or whether to pause or freeze adaptation for a period of time,
may be based upon detection of noise field characteristics, in some
examples. For instance, some examples may use beamforming to
provide the primary signal and less aggressive adaptation when the
noise field is detected to be more diffuse, and may use an
omni-directional microphone to provide the primary signal and more
aggressive adaptation when the noise field is detected to be more
discrete. Determination of the diffusivity of the noise field may
be determined, in some examples, by calculating or determining a
magnitude-squared coherence between various microphone channels. In
some examples, a magnitude-squared coherence is determined for
frequencies expected to have a low coherence for diffuse noise
fields, e.g., nulls in a characteristic sinc function.
[0061] Various examples of systems and methods in accord with those
described herein may include one or more acoustic drivers for the
production of acoustic signals from one or more program content
signals. For example, an audio system may include one or more
loudspeakers in addition to multiple microphones, such as the
microphones 210, 220 of any of the above described example audio
systems, or combinations or alternatives thereof, and may receive a
program content signal for playback as an acoustic signal. Such an
audio system may be a speakerphone system, a portable speaker, a
virtual assistant device, a soundbar, etc. and may be coupled via a
wireless connection, e.g., Bluetooth.TM. or wi-fi, or a wired
connection, e.g., optical, coaxial, Ethernet, using any of various
protocols and/or signal formats, to audio signal sources, such as a
smartphone, a television, a remote server, or the like. The
loudspeaker(s) of the example audio system described may be an
alternate audio source providing acoustic signals that are not
desired to be part of an output signal, e.g., the output signal
240. In some examples, operation of the adaptive filters 232 upon
signals from the reference microphones 220 may sufficiently reduce
audio program content (e.g., from the program content signal(s)
being converted to one or more acoustic signals by one or more
loudspeakers) from the primary signal 212 to provide a sufficient
output signal 240. In other examples, an echo cancelation subsystem
may be included that removes some or all of the rendered program
content from the primary signal 212 or from one or more of the
reference signals 222 to substantially remove or reduce components
of the program content signal from being present in the output
signal 240.
[0062] Various examples of the systems and methods in accord with
those described herein may include variations to operation,
components, and features based upon application or environment. For
example, an audio system designed for portable use may include an
option to operate from battery power at times, and the number of
reference microphones (e.g., adaptive channels), adaptive filters,
sub-bands, sampling frequency, and the like, may be selected or may
be adapted to reduce power consumption in certain examples. In some
examples, tradeoffs to reduce power consumption may be made on the
fly by the system, and may include trading off performance in terms
of noise reduction for an extended operating time (e.g., battery
life). Such options may be configurable by the user in certain
examples. Additionally, such options may be changed over time,
e.g., as a battery charge level reduces below one or more
thresholds, for example. An audio system expected to be used in a
more fixed environment, such as a home or office speaker that may
be plugged in and may be expected to remain in a fixed position for
an extended period of time, may be designed for more robust
operation at the expense of increased power consumption, for
instance, at least in part due to the expected reliability and
sufficiency of power from, e.g., an electric grid. In such cases,
the system may use more reference microphones (e.g., more
channels), more adaptive filters (perhaps with higher resolution),
higher sampling frequency, more sub-bands, etc., to provide more
robust performance without concern for power consumption. Some
examples may incorporate expected knowledge regarding the acoustic
environment. For example, a portable system may be expected to
perform in a more widely varying and/or changing acoustic
environment while a non-portable (though moveable) system may be
expected to operate among a more limited set of conditions that may
not change much over time. Accordingly, a non-portable system may
maintain or store adapted filter weights, e.g., when powered off,
to use again at the next power-on event. A portable system may not
benefit from storing previously converged filter weights because
there may be no expectation that it will be turned on in the same
acoustic environment as it was previously operated. A portable
sytem operating on battery power may be more likely to be outside,
with few reflected or reverberant signals, whereas a non-portable
system may be expected to be inside, with walls nearby, having
relatively strong noise signals from multiple directions.
Accordingly, in various examples, various configurations including
operational parameters, power consumption, processing resources,
memory, etc. may be selected or chosen based upon one or more
expected use scenarios and/or expected acoustic environments.
[0063] One or more of the above described systems and methods, in
various examples and combinations, may be used to capture the voice
of a user and isolate or enhance the user's voice relative to
additional acoustic sources and background noise. Any of the
systems and methods described, and variations thereof, may be
implemented with varying levels of reliability based on, e.g.,
microphone quality, microphone placement, acoustic ports,
structural or device frame design, threshold values, selection of
adaptive, spectral, and other algorithms, weighting factors, window
sizes, filter resolutions, sub-band frequency widths, etc., as well
as other criteria that may accommodate varying applications and
operational parameters.
[0064] It should be understood that many of the functions, methods,
and/or components of the systems disclosed herein according to
various aspects and examples may be implemented or carried out in a
digital signal processor (DSP) and/or other circuitry, analog or
digital, suitable for performing signal processing and other
functions in accord with the aspects and examples disclosed herein.
Additionally or alternatively, a microprocessor, a logic
controller, logic circuits, field programmable gate array(s)
(FPGA), application-specific integrated circuit(s) (ASIC), general
computing processor(s), micro-controller(s), and the like, or any
combination of these, may be suitable, and may include analog or
digital circuit components and/or other components with respect to
any particular implementation
[0065] Functions and components disclosed herein may operate in the
digital domain, the analog domain, or a combination of the two, and
certain examples include analog-to-digital converter(s) (ADC)
and/or digital-to-analog converter(s) (DAC) where appropriate,
despite the lack of illustration of ADC's or DAC's in the various
figures. Further, functions and components disclosed herein may
operate in a time domain, a frequency domain, or a combination of
the two, and certain examples include various forms of Fourier or
similar analysis, synthesis, and/or transforms to accommodate
processing in the various domains.
[0066] Any suitable hardware and/or software, including firmware
and the like, may be configured to carry out or implement
components of the aspects and examples disclosed herein, and
various implementations of aspects and examples may include
components and/or functionality in addition to those disclosed.
Various implementations may include stored instructions for a
digital signal processor and/or other circuitry to enable the
circuitry, at least in part, to perform the functions described
herein.
[0067] It should be understood that an acoustic transducer,
microphone, driver, or loudspeaker, may be any of many types of
transducers known in the art. For example, an acoustic structure
coupled to a coil positioned in a magnetic field, to cause
electrical signals in response to motion, or to cause motion in
response to electrical signals, may be a suitable acoustic
transducer. Additionally, a piezoelectric material may respond in
manners to convert acoustical signals to electrical signals, and
the reverse, and may be a suitable acoustic transducer. Further,
micro-electrical mechanical systems (MEMS) may be employed as, or
be a component for, a suitable acoustic transducer. Any of these or
other forms of acoustic transducers may be suitable and included in
various examples.
[0068] Having described above several aspects of at least one
example, it is to be appreciated various alterations,
modifications, and improvements will readily occur to those skilled
in the art. Such alterations, modifications, and improvements are
intended to be part of this disclosure and are intended to be
within the scope of the invention. Accordingly, the foregoing
description and drawings are by way of example only, and the scope
of the invention should be determined from proper construction of
the appended claims, and their equivalents.
* * * * *