CN113889136A - Pickup method, pickup device and storage medium based on microphone array - Google Patents

Pickup method, pickup device and storage medium based on microphone array Download PDF

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Publication number
CN113889136A
CN113889136A CN202111073426.6A CN202111073426A CN113889136A CN 113889136 A CN113889136 A CN 113889136A CN 202111073426 A CN202111073426 A CN 202111073426A CN 113889136 A CN113889136 A CN 113889136A
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microphone
microphone array
error
pickup method
sound pickup
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蔡野锋
叶超
马登永
沐永生
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Zhongke Shangsheng Suzhou Electronics Co ltd
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Zhongke Shangsheng Suzhou Electronics Co ltd
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L21/0264—Noise filtering characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G10L2021/02161—Number of inputs available containing the signal or the noise to be suppressed
    • G10L2021/02166—Microphone arrays; Beamforming

Abstract

The invention discloses a pickup method, a pickup device and a storage medium based on a microphone array. A pickup method based on a microphone array comprises the following steps: A. determining a microphone array having a plurality of microphone channels, each of the microphone channels including at least one microphone unit; B. the error probability model is built up as follows,
Figure DDA0003261229870000011
Figure DDA0003261229870000012
representing an actual steering vector; C. constructing an optimal problem of a differential beam design algorithm based on the error probability model; D. solving an optimal solution of the optimal problem to obtain weight vectors of a plurality of microphone channels of the microphone array; E. according to whatAnd the weight vector adjusts the voice signals collected by the microphone array and outputs optimized voice signals. The sound pickup method has good anti-interference performance, particularly has good directivity at low frequency, and has low distortion.

Description

Pickup method, pickup device and storage medium based on microphone array
Technical Field
The invention belongs to the field of microphone array pickup, and relates to a pickup method, a pickup device and a storage medium based on a microphone array.
Background
In a complex acoustic environment, factors such as background noise, interference and reverberation deteriorate the pickup performance of a microphone, and the definition and intelligibility of voice are reduced, so that the pickup of a single microphone cannot meet daily requirements. Compared with the single-microphone pickup effect, the microphone array combined with the beam forming algorithm can enhance the signal from the target direction, inhibit the gain of the signal in the non-target direction, improve the signal-to-noise ratio of the output voice and improve the voice quality by fusing the space-time information, so that the microphone array is widely applied to the fields of voice enhancement, voice recognition and the like.
The differential beam forming design algorithm has the advantages of small aperture, high directivity index and the like, can realize the broadband constant beam width and effectively reduce the voice distortion degree, and therefore, the differential beam forming design algorithm obtains wide attention in a plurality of fixed beam forming design algorithms. However, the filter response has the problem of white noise amplification, so that the system is sensitive to inevitable errors such as self noise and mismatching of the microphone, and the performance is extremely deteriorated in practice.
Disclosure of Invention
The invention aims to provide a pickup method of a microphone array, which has better anti-interference performance, especially has better directivity at low frequency and low distortion.
Another object of the present invention is to provide a sound pickup apparatus which is small in size, has good interference resistance, and has a low degree of distortion.
It is still another object of the present invention to provide a computer-readable storage medium storing the sound pickup method of the microphone array described above.
According to a first aspect of the invention, a microphone array based sound pickup method comprises the following steps:
A. determining a microphone array having a plurality of microphone channels, each of the microphone channels including at least one microphone unit;
B. the error probability model is built up as follows,
Figure BDA0003261229850000011
wherein the content of the first and second substances,
Figure BDA0003261229850000021
representing an actual steering vector;
ideal guide vector
Figure BDA0003261229850000022
Where θ is the plane wave propagation direction, δ is the spacing between adjacent microphone array units, τ0δ/c is the time delay of plane waves in the direction of 0 degree to reach two adjacent microphone units, c is the sound propagation speed, j is an imaginary index, and ω is an angular frequency; an element indicates a dot product;
amul(ω) represents a random multiplicative error with a magnitude of M × 1, M representing the number of microphone channels, where the M-th element is
Figure BDA0003261229850000023
The magnitude of the multiplicative error is represented,
Figure BDA0003261229850000024
representing a multiplicative error phase;
aadd(ω) represents a random additive error of size M × 1, where the M-th element is
Figure BDA0003261229850000025
The magnitude of the additive error is represented,
Figure BDA0003261229850000026
representing an additive error phase;
C. constructing an optimal problem of a differential beam design algorithm based on the error probability model;
D. solving an optimal solution of the optimal problem to obtain weight vectors of a plurality of microphone channels of the microphone array;
E. and adjusting the voice signals collected by the microphone array according to the weight vectors, and outputting the optimized voice signals.
According to a preferred embodiment, in step C, the optimization problem is expressed as follows:
Figure BDA0003261229850000027
where E { } is the desired average, H (ω) ═ H1(ω),H2(ω),…,HM(ω)]TFor the weight vector, the weight of the mth microphone channel
Figure BDA0003261229850000028
Superscripts and H denote conjugate and conjugate transpose, respectively, and α ═ θN,1,…,θN,N]TFor the N zero-point position vectors,
Figure BDA0003261229850000029
the definition is as follows:
Figure BDA00032612298500000210
wherein the elements
Figure BDA00032612298500000211
Represents the zero point position θ obtained according to the formula (i)N,1N satisfies that M is more than or equal to N + 1; and the other elements are analogized.
More preferably, in step D, the optimal solution is:
hopt(ω)＝R-1(ω)CH(ω)[C(ω)R-1(ω)CH(ω)]-1
r (omega) and C (omega) are each defined as
R(ω)＝(DH(ω,α)D(ω,α))⊙R1+N*R2+R3；
Figure BDA0003261229850000031
Wherein the content of the first and second substances,
Figure BDA0003261229850000032
Figure BDA0003261229850000033
Figure BDA0003261229850000034
Figure BDA0003261229850000035
re is the operation of taking the real part of the element,
Figure BDA0003261229850000036
is the desired value of the squared magnitude of the multiplicative error
Figure BDA0003261229850000037
Is the expected value of the amplitude of the multiplicative error
Figure BDA0003261229850000038
Figure BDA0003261229850000039
Figure BDA00032612298500000310
Is additive errorExpected value of the square of the magnitude of the difference
Figure BDA00032612298500000311
For the expected value of the amplitude of the additive error
Figure BDA00032612298500000312
Figure BDA00032612298500000313
Figure BDA00032612298500000314
And
Figure BDA00032612298500000315
respectively representing the probability density distribution functions of the multiplicative error magnitude and phase,
Figure BDA00032612298500000316
and
Figure BDA00032612298500000317
probability density distribution function representing the amplitude and phase of additive error, respectively, d (a)mul(ω)) represents amulDifferential of (ω), d (φ)mul(ω)) represents φmulDifferential of (ω), d (a)add(ω)) represents aaddDifferential of (ω), d (φ)add(ω)) represents φaddThe differential of (omega) is obtained by the following steps,
Dn,mand (ω, α) is expressed as an element where the subscript of matrix D (ω, α) is (N, M), N is 1, …, N, M is 1, …, M.
According to a preferred embodiment, the inner probability density distribution function of the amplitude and phase of the multiplicative error and/or the inner probability density distribution function of the amplitude and phase of the additive error coincide.
According to a preferred embodiment, the inner probability density distribution function of the amplitude and phase of the multiplicative error and the inner probability density distribution function of the amplitude and phase of the additive error are obtained by modeling or actual measurement.
According to a preferred embodiment, in step a, the microphone units are uniformly and linearly arranged to form a linear microphone array.
More preferably, N zero position vectors α ═ θ are determinedN,1,…,θN,N]TThe superscript T is transposed, and the zero point position is required to satisfy 0 & ltthetaN,1＜θN,2＜…＜θN,NLess than 180, and the number of the target direction needs to meet the condition that M is more than or equal to N +1, and the desired target direction is a 0-degree direction.
According to a preferred embodiment, in step E, the signals collected by the microphone array are converted into a frequency domain, multiplied by the weight vector, and then superimposed, and then converted into a time domain through an inverse fourier transform, and the time domain outputs an optimized speech signal.
According to a second aspect of the present invention, a sound pickup apparatus includes a microphone array, a digital-to-analog conversion mechanism, and a signal processing mechanism including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the sound pickup method as described above when executing the program.
According to a third aspect of the present invention, a computer-readable storage medium is characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the sound pickup method as described above.
Compared with the prior art, the invention has the following advantages by adopting the scheme:
according to the pickup method based on the microphone array, the difference design algorithm based on the zero energy constraint of the error probability model is adopted, the probability modeling is carried out on the self-noise, mismatching and other errors of the microphone, the expected value is optimized, the anti-interference performance of the algorithm can be further improved, and particularly, the algorithm still has a good directional effect at a low frequency, is strong in anti-interference performance, flat in frequency response, low in distortion degree and good in robustness; meanwhile, the pickup device adopting the method has smaller size, keeps better directivity and is convenient to install.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a flow chart of a method for picking up sound according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a microphone array according to an embodiment of the invention;
FIG. 3a and FIG. 3b are a white noise gain curve and an average expected frequency response curve in the 0 degree direction, respectively, of the sound pickup method according to the embodiment of the present invention;
FIGS. 4a and 4b show the average desired beam patterns at 500Hz and 3000Hz for the two algorithms, respectively;
fig. 5 is a block diagram of a sound pickup apparatus according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the advantages and features of the invention may be more readily understood by those skilled in the art. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto.
The embodiment provides a pickup method of a microphone array, which adopts a differential design algorithm based on zero energy constraint of an error probability model, and the algorithm optimizes an expected value by performing probability modeling on errors such as self noise, mismatching and the like of a microphone, so that the anti-interference performance of the algorithm can be further improved. As shown in fig. 1, the sound pickup method includes: step A, determining a microphone array, wherein the microphone array is provided with a plurality of microphone channels, and each microphone channel comprises at least one microphone unit; B. establishing an error probability model of the microphone array; C. constructing an optimal problem of a differential beam design algorithm based on the error probability model; D. solving an optimal solution of the optimal problem to obtain weight vectors of a plurality of microphone channels of the microphone array; E. and adjusting the voice signals collected by the microphone array according to the weight vectors, and outputting the optimized voice signals. The details are as follows.
First, referring to fig. 2, the microphone array is a linear array including M microphone units uniformly distributed, thereby having M microphone channels, X (ω) is a speech signal of a speaker, and Y is a signal of a speaker1(ω)、Y2(ω)、Y3And (ω) are the speech signals picked up by the microphone units 1, 2, M, respectively. According to actual requirements, determining the number M of the microphone units of the uniformly distributed linear array, and simultaneously determining N zero position vectors alpha [ theta ]N,1,…,θN,N]TThe superscript T is transposed, and the zero point position is required to satisfy 0 & ltthetaN,1＜θN,2＜…＜θN,NLess than 180, and the number of the target direction needs to meet the condition that M is more than or equal to N +1, and the desired target direction is a 0-degree direction.
Secondly, establishing an actual guide vector
Figure BDA0003261229850000061
The model is as follows:
Figure BDA0003261229850000062
Figure BDA0003261229850000063
is an ideal guide vector, wherein theta is the plane wave propagation direction, delta is the adjacent distance of the microphone array units, and tau0δ/c is the delay of a plane wave in the 0 degree direction to reach two adjacent microphones, c is the acoustic propagation velocity, j is the imaginary index, and ω is the angular frequency.
An element indicates a dot product ofmul(ω) is the random multiplicative error, with a magnitude Mx1, where the m-th element is
Figure BDA0003261229850000064
Figure BDA0003261229850000065
For multiplicative error magnitudes, the internal probability distribution functions are the same,
Figure BDA0003261229850000066
for multiplicative error phase, the internal probability distribution function is the same, aadd(ω) is the random additive error, with magnitude Mx1, where the m-th element is
Figure BDA0003261229850000067
For additive error magnitudes, the internal probability distribution functions are the same,
Figure BDA0003261229850000068
for additive error phase, the internal probability distribution functions are the same, and all the above random variables are independent of each other.
These probability distributions may be obtained by modeling, or by actual measurement.
Thirdly, expressing the optimal problem of the improved zero energy constraint differential beam design algorithm based on the error probability distribution model as follows:
Figure BDA0003261229850000069
s.t.
Figure BDA00032612298500000610
e {. is the desired average, H (ω) ═ H1(ω),H2(ω),…,HM(ω)]TIn order to be a weight vector, the weight vector,
Figure BDA00032612298500000611
for the weight of the mth microphone channel, superscript x and H are the conjugate and conjugate transpose, respectively,
Figure BDA00032612298500000612
is defined as:
Figure BDA00032612298500000613
fourthly, the optimal solution h of the optimization problemopt(ω) is:
hopt(ω)＝R-1(ω)CH(ω)[C(ω)R-1(ω)CH(ω)]-1
r (ω) is defined as:
R(ω)＝(DH(ω,α)D(ω,α))⊙R1+N*R2+R3
c (ω) is defined as:
Figure BDA0003261229850000071
wherein
Figure BDA0003261229850000072
Dn,m(ω, α) is expressed as the element where the subscript of matrix D (ω, α) is (N, M), N is 1, …, N, M is 1, …, M
Figure BDA0003261229850000073
Figure BDA0003261229850000074
Figure BDA0003261229850000075
Re {. is an operation of taking a real part of an element,
Figure BDA0003261229850000076
period of squared multiplicative error magnitudeInspection value
Figure BDA0003261229850000077
Is the expected value of the amplitude of the multiplicative error
Figure BDA0003261229850000078
Figure BDA0003261229850000079
Figure BDA00032612298500000710
Is the expected value of the square of the amplitude of the additive error
Figure BDA00032612298500000711
For the expected value of the amplitude of the additive error
Figure BDA00032612298500000712
Figure BDA0003261229850000081
Figure BDA0003261229850000082
And
Figure BDA0003261229850000083
probability density distribution functions of the amplitude and phase of the multiplicative error, respectively, since the distribution of each element in the multiplicative random error vector is the same, the amplitude or phase index of the error is given an omission,
Figure BDA0003261229850000084
and
Figure BDA0003261229850000085
probability density distribution function representing the amplitude and phase of additive error, respectively, d (a)mul(ω)) represents amulDifferential of (ω), d (φ)mul(ω)) represents φmulDifferential of (ω), d (a)add(ω)) represents aaddDifferential of (ω), d (φ)add(ω)) represents φaddThe differential of (ω), which can be defined similarly
Figure BDA0003261229850000086
Figure BDA0003261229850000087
Dn,mAnd (ω, α) is expressed as an element where the subscript of matrix D (ω, α) is (N, M), N is 1, …, N, M is 1, …, M.
And fifthly, converting the signals collected by the microphone array to a frequency domain, multiplying the frequency domain signals by the weight vector, superposing the multiplied frequency domain signals, and converting the multiplied frequency domain signals into time domain signals through inverse Fourier transform to output optimized voice signals.
Simulation example
A quaternary linear microphone array is adopted, the distance between adjacent microphone units is 1cm, the considered frequency range is [100,3700] Hz, the speech sound frequency range is covered, the distance is far smaller than the wavelength of sound waves, and the requirement of a differential array is met. Assuming that the pilot vector has multiplication error and additive error simultaneously, the amplitude range of the multiplicative error is uniformly distributed between [0.85,1.15], the phase error is uniformly distributed between [ -5,5] degrees, the amplitude range of the additive error is uniformly distributed between [0,0.01], and the phase is uniformly distributed between [ -180,180] degrees. A second order hypercardioid pattern was selected as the target beam pattern with null positions of 106 and 153 degrees and a target direction of 0 degrees. Beamforming is performed by using a robustness design method based on minimum norm and error probability distribution proposed herein, wherein the second-order hypercardioid pattern and the minimum norm method are shown in "Chen, jingdong.Benesty, Jacob.Pan, Chao.on the design and implementation of linear differential microphone arrays.J.Acoust.Soc.Am., Vol.136, No.6, Dec.2014"
The evaluation indexes are White Noise Gain (WNG), an average expected beam pattern and an average expected frequency response of the target direction, wherein the WNG is used for describing the capability of the system to resist systematic errors such as microphone self-noise, mismatching and the like, and the larger the value of the WNG is, the stronger the error resistance performance is, which is defined as:
Figure BDA0003261229850000088
the average desired beam pattern is defined as
Figure BDA0003261229850000089
I.e. the frequency omega is not changed, the value range of theta is [ -180,180,]degree, and the average expected frequency response of the target direction is also expressed as
Figure BDA0003261229850000091
However, in this case, θ is 0 degrees and the frequency ω is within a range of [100,3700]]Hz. The average value is simulated by a Monte Carlo method, and the average value is taken after the error is randomly generated for 1000 times.
As shown in fig. 3a and fig. 3b, the algorithm of the present embodiment has a significant improvement in WNG performance, and the average expected frequency response is very flat; the frequency response of the method based on the minimum norm is obviously boosted at low frequency, and compared with the maximum boosted frequency of 35dB at high frequency, the method is easy to cause voice distortion.
FIGS. 4a and 4b show the average expected beam patterns for the two algorithms at 500Hz and 3000Hz, respectively, and it can be seen that the minimum norm method is substantially ineffective at 500Hz and is non-directional; whereas the probabilistic error based approach still has a 10dB attenuation effect in the 180 degree direction. At 3000Hz, compared with the minimum norm method, the probability error-based method has a slightly wider main lobe and a slightly lower side lobe.
The embodiment also provides a sound pickup device. Referring to fig. 5, the sound pickup apparatus includes a microphone array, a digital-to-analog conversion mechanism, and a signal processing mechanism; the microphone array is used for collecting the voice of a speaker, the digital-analog conversion mechanism is used for converting voice signals collected by the microphone array into digital signals, and the signal processing mechanism adopts the algorithm to optimize the digital signals output by the digital-analog conversion mechanism and outputs the optimized voice signals.
The microphone array comprises a plurality of microphone units which are linearly arranged and are equally spaced; specifically, in this embodiment, the pitch between adjacent microphone units is 1 cm. The digital-to-analog conversion mechanism is a multi-channel ADC digital-to-analog conversion chip, and the input end of the multi-channel ADC digital-to-analog conversion chip is electrically connected with the microphone array. The signal processing mechanism adopts a DSP processing chip or an FPGA processing chip which is electrically connected with the output end of the digital-analog conversion mechanism. Specifically, the signal processing mechanism includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the sound pickup method as described above when executing the program.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program that, when executed by a processor, implements the sound pickup method as described above.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are preferred embodiments, which are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.

Claims (10)

1. A pickup method based on a microphone array is characterized by comprising the following steps:
A. determining a microphone array having a plurality of microphone channels, each of the microphone channels including at least one microphone unit;
B. the error probability model is built up as follows,
Figure FDA0003261229840000011
wherein the content of the first and second substances,
Figure FDA0003261229840000012
representing an actual steering vector;
ideal guide vector
Figure FDA0003261229840000013
Where θ is the plane wave propagation direction, δ is the spacing between adjacent microphone array units, τ0δ/c is the time delay of plane waves in the direction of 0 degree to reach two adjacent microphone units, c is the sound propagation speed, j is an imaginary index, and ω is an angular frequency; an element indicates a dot product;
amul(ω) represents a random multiplicative error with a magnitude of M × 1, M representing the number of microphone channels, where the M-th element is
Figure FDA0003261229840000014
Figure FDA0003261229840000015
The magnitude of the multiplicative error is represented,
Figure FDA0003261229840000016
representing a multiplicative error phase;
aadd(ω) represents a random additive error of size M × 1, where the M-th element is
Figure FDA0003261229840000017
Figure FDA0003261229840000018
The magnitude of the additive error is represented,
Figure FDA0003261229840000019
representing an additive error phase;
C. constructing an optimal problem of a differential beam design algorithm based on the error probability model;
D. solving an optimal solution of the optimal problem to obtain weight vectors of a plurality of microphone channels of the microphone array;
E. and adjusting the voice signals collected by the microphone array according to the weight vectors, and outputting the optimized voice signals.
2. The sound pickup method according to claim 1, wherein in step C, the optimal problem is expressed as follows:
Figure FDA00032612298400000110
where E { } is the desired average, H (ω) ═ H1(ω),H2(ω),…,HM(ω)]TFor the weight vector, the weight of the mth microphone channel
Figure FDA00032612298400000111
Superscripts and H denote conjugate and conjugate transpose, respectively, and α ═ θN,1,…,θN,N]TFor the N zero-point position vectors,
Figure FDA00032612298400000112
the definition is as follows:
Figure FDA0003261229840000021
wherein the elements
Figure FDA0003261229840000022
Represents the zero point position θ obtained according to the formula (i)N,1N satisfies that M is more than or equal to N + 1; and the other elements are analogized.
3. The sound pickup method according to claim 2, wherein in step D, the optimal solution is:
hopt(ω)＝R-1(ω)CH(ω)[C(ω)R-1(ω)CH(ω)]-1
r (omega) and C (omega) are each defined as
Figure FDA0003261229840000023
Wherein the content of the first and second substances,
Figure FDA0003261229840000024
Figure FDA0003261229840000025
Figure FDA0003261229840000026
Figure FDA0003261229840000027
re is the operation of taking the real part of the element,
Figure FDA0003261229840000028
Figure FDA0003261229840000029
Figure FDA00032612298400000210
Figure FDA00032612298400000211
Figure FDA00032612298400000212
Figure FDA0003261229840000031
Figure FDA0003261229840000032
Figure FDA0003261229840000033
Figure FDA0003261229840000034
and
Figure FDA0003261229840000035
respectively representing the probability density distribution functions of the multiplicative error magnitude and phase,
Figure FDA0003261229840000036
and
Figure FDA0003261229840000037
respectively representing additive error amplitude and phaseD (a) is a probability density distribution function ofmul(ω)) represents amulDifferential of (ω), d (φ)mul(ω)) represents φmulDifferential of (ω), d (a)add(ω)) represents aaddDifferential of (ω), d (φ)add(ω)) represents φaddThe differential of (omega) is obtained by the following steps,
Dn,mand (ω, α) is expressed as an element where the subscript of matrix D (ω, α) is (N, M), N is 1, …, N, M is 1, …, M.
4. The sound pickup method according to claim 1, wherein an internal probability density distribution function of the amplitude and the phase of the multiplicative error coincide with each other, and/or an internal probability density distribution function of the amplitude and the phase of the additive error coincide with each other.
5. The sound pickup method according to claim 1 or 4, wherein an internal probability density distribution function of the amplitude and phase of the multiplicative error and an internal probability density distribution function of the amplitude and phase of the additive error are obtained by modeling or actual measurement.
6. The sound pickup method according to claim 1, wherein in step a, the microphone units are uniformly and linearly arranged to form a linear microphone array.
7. The sound pickup method according to claim 6, wherein N zero point position vectors α ═ θ are determinedN,1,…,θN,N]TThe superscript T is transposed, and the zero point position is required to satisfy 0 & ltthetaN,1＜θN,2＜…＜θN,NLess than 180, and the number of the target direction needs to meet the condition that M is more than or equal to N +1, and the desired target direction is a 0-degree direction.
8. The sound pickup method according to claim 1, wherein in step E, the signals collected by the microphone array are converted into a frequency domain, multiplied by the weight vectors, superimposed, and then converted into a time domain by an inverse fourier transform to output an optimized speech signal.
9. A sound pickup apparatus comprising a microphone array, a digital-to-analog conversion mechanism, and a signal processing mechanism including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the sound pickup method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when being executed by a processor, implements the sound pickup method according to any one of claims 1 to 8.
CN202111073426.6A 2021-09-14 2021-09-14 Pickup method, pickup device and storage medium based on microphone array Pending CN113889136A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114923136A (en) * 2022-07-15 2022-08-19 安徽云磬科技产业发展有限公司 Multi-array pipeline leakage positioning method and device
CN115278449A (en) * 2022-09-26 2022-11-01 中国飞行试验研究院 Method, device and equipment for determining coordinates of microphone array unit and storage medium

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114923136A (en) * 2022-07-15 2022-08-19 安徽云磬科技产业发展有限公司 Multi-array pipeline leakage positioning method and device
CN115278449A (en) * 2022-09-26 2022-11-01 中国飞行试验研究院 Method, device and equipment for determining coordinates of microphone array unit and storage medium
CN115278449B (en) * 2022-09-26 2023-03-10 中国飞行试验研究院 Method, device and equipment for determining coordinates of microphone array unit and storage medium

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