CN110786022A - Wind noise processing method, device, system and storage medium based on multiple microphones - Google Patents

Abstract

The application provides a multi-microphone-based wind noise processing method, device and system and a storage medium. The method comprises the following steps: respectively acquiring a first digital signal from K microphones, wherein K is an integer greater than 1; for each first digital signal, carrying out separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum; wind noise restoration processing is carried out on the first signal transform domain spectrum to obtain a third signal transform domain spectrum; combining the third signal transform domain spectrum and the second signal transform domain spectrum to obtain a first transform domain spectrum; and reconstructing the first transform domain spectrum to obtain a second digital signal, so that wind noise interference can be reduced on one hand, and signal distortion can be prevented on the other hand.

Description

Wind noise processing method, device, system and storage medium based on multiple microphones

technical field

The embodiments of the present application relate to the field of noise reduction technologies, and in particular, to a method, device, system, and storage medium for wind noise processing based on multiple microphones.

Background technique

Wind noise is caused by air turbulence near the pickup site of the microphone, which is converted into turbulent pressure fluctuations that are picked up by the microphone along with the sound waves. Since this fluctuation is often much larger than the sound wave, it will cause a large distortion of the recorded signal from the microphone. Wind noise is very common when using microphones for audio capture outdoors. It has a great impact on the quality of the recording and will greatly destroy the fidelity of the recording.

At present, the method to overcome the interference of wind noise in recording is to use physical protection to avoid air turbulence at the pickup part of the microphone, such as wrapping the microphone with a windproof sponge ball or a windproof hair ball. However, although this method can effectively reduce wind noise interference, But at the same time, the high frequency signal is greatly attenuated and the signal is distorted.

SUMMARY OF THE INVENTION

Embodiments of the present application provide a multi-microphone-based wind noise processing method, device, system, and storage medium. The technical solution of the present application can reduce wind noise interference on the one hand, and prevent signal distortion on the other hand.

In a first aspect, the present application provides a method for processing wind noise based on multiple microphones, including: acquiring a first digital signal from K microphones, where K is an integer greater than 1; The digital signal is separated and processed to obtain a first signal transform domain spectrum and a second signal transform domain spectrum; wind noise repair processing is performed on the first signal transform domain spectrum to obtain a third signal transform domain spectrum; Combine with the transform domain spectrum of the second signal to obtain a first transform domain spectrum; perform reconstruction processing on the first transform domain spectrum to obtain a second digital signal.

In a second aspect, the present application provides a multi-microphone-based wind noise processing device, including: an acquisition module, a separation processing module, a wind noise restoration processing module, a merging module, and a reconstruction processing module. The obtaining module is used to obtain a first digital signal from K microphones respectively, where K is an integer greater than 1; the separation processing module is used to separate and process the first digital signal for each first digital signal to obtain a first digital signal. a signal transform domain spectrum and a second signal transform domain spectrum; the wind noise repair processing module is used to perform wind noise repair processing on the first signal transform domain spectrum to obtain a third signal transform domain spectrum; the merging module is used to transform the third signal The domain spectrum is combined with the transform domain spectrum of the second signal to obtain the first transform domain spectrum; the reconstruction processing module is used for reconstructing the first transform domain spectrum to obtain the second digital signal.

In a third aspect, the present application provides a multi-microphone-based wind noise processing device, comprising: a processing unit and K first filters, wherein the processing units are respectively connected with the K first filters; the processing units are used for: respectively: Obtain a first digital signal from K microphones, where K is an integer greater than 1; for each first digital signal, separate and process the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum Perform wind noise repair processing on the first signal transform domain spectrum to obtain a third signal transform domain spectrum; combine the third signal transform domain spectrum with the second signal transform domain spectrum to obtain the first transform domain spectrum; the first filter is used for Reconstruction processing is performed on the first transform domain spectrum to obtain a second digital signal.

In a fourth aspect, the present application provides a multi-microphone-based wind noise processing system, comprising: the wind noise processing device according to the second aspect and K microphones; wherein the K microphones are connected to the wind noise processing device.

In a fifth aspect, the present application provides a multi-microphone-based wind noise processing system, comprising: the wind noise processing device according to the third aspect and K microphones; wherein the K microphones are connected to the wind noise processing device.

In a sixth aspect, the present application provides a computer storage medium, comprising: computer instructions, where the computer instructions are used to implement the above-mentioned multi-microphone-based wind noise processing method.

In a seventh aspect, the present application provides a computer program product, comprising: computer instructions, where the computer instructions are used to implement the above-mentioned multi-microphone-based wind noise processing method.

The present application provides a method, device, system and storage medium for wind noise processing based on multiple microphones. Including: obtaining a first digital signal from K microphones respectively, where K is an integer greater than 1; for each first digital signal, performing separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum; perform wind noise repair processing on the first signal transform domain spectrum to obtain a third signal transform domain spectrum; combine the third signal transform domain spectrum with the second signal transform domain spectrum to obtain a first transform domain spectrum; A transform domain spectrum is reconstructed to obtain a second digital signal. The technical solution of the present application can reduce wind noise interference on the one hand, and prevent signal distortion on the other hand.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the accompanying drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative labor.

1 is an application scenario diagram of the technical solution of the application;

FIG. 2 is a flowchart of a method for processing wind noise based on multiple microphones according to an embodiment of the present application;

3 is a flowchart of a multi-microphone-based wind noise processing method provided by another embodiment of the present application;

FIG. 4 is a flowchart of a method for processing wind noise based on multiple microphones according to still another embodiment of the present application;

5 is a flowchart of a method for processing wind noise based on multiple microphones provided by another embodiment of the present application;

FIG. 6 is a flowchart of a method for processing wind noise based on multiple microphones according to still another embodiment of the present application;

7 is a signal waveform diagram of a dual microphone provided by an embodiment of the present application under the condition of being interfered by wind noise;

FIG. 8 is a signal waveform diagram of a dual microphone provided by an embodiment of the present application after wind noise processing;

FIG. 9 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 90 according to an embodiment of the present application;

FIG. 10 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 100 according to an embodiment of the present application;

FIG. 11 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 110 according to an embodiment of the present application;

FIG. 12 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 120 according to an embodiment of the present application;

FIG. 13 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 130 according to an embodiment of the present application;

FIG. 14 is a schematic diagram of a multi-microphone-based wind noise processing system 140 according to an embodiment of the present application;

FIG. 15 is a schematic diagram of a multi-microphone-based wind noise processing system 150 according to an embodiment of the present application.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

As mentioned above, the current method to overcome the interference of wind noise in recording is to use physical protection methods to avoid air turbulence at the pickup part of the microphone, such as wrapping the microphone with a windproof sponge ball or a windproof hair ball. However, although this method can effectively reduce the Wind noise interference, but at the same time cause great attenuation of high-frequency signals, and cause signal distortion. In order to solve the technical problem, the present application provides a multi-microphone-based wind noise processing method, device, system and storage medium.

FIG. 1 is an application scenario diagram of the technical solution of the present application. As shown in FIG. 1 , the wind noise processing device 11 can obtain a first digital signal from K microphones 12, K is an integer greater than 1, and the K first digital signals are Wind noise processing is performed on the digital signal. The technical solution of the present application will be described in detail below with reference to the application scenario diagram shown in FIG. 1 .

2 is a flowchart of a multi-microphone-based wind noise processing method according to an embodiment of the present application. The execution body of the method is a wind noise processing device, and the wind noise processing device may be a computer, tablet computer, mobile phone or other intelligent part or all of the device. As shown in Figure 2, the method includes the following steps:

Step S21 : the wind noise processing apparatus obtains a first digital signal from the K microphones, where K is an integer greater than 1.

Step S22: For each first digital signal, the wind noise processing apparatus performs separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum.

Step S23: The wind noise processing apparatus performs wind noise repair processing on the first signal transform domain spectrum to obtain a third signal transform domain spectrum.

Step S24: The wind noise processing apparatus combines the third signal transform domain spectrum with the second signal transform domain spectrum to obtain the first transform domain spectrum.

Step S25: The wind noise processing apparatus performs reconstruction processing on the first transform domain spectrum to obtain a second digital signal.

Describe step S21:

Optionally, the wind noise processing apparatus may collect signals from K microphones to obtain K first digital signals, which are respectively denoted as x ₁ (t), x ₂ (t)...x _K (t), where t represents time. The K first digital signals may be the same or different, which is not limited in this embodiment of the present application. The sampling frequencies of the K first digital signals are the same, and the sampling frequency is denoted as fs.

Describe step S22:

Optionally, FIG. 3 is a flowchart of a method for processing wind noise based on multiple microphones provided by another embodiment of the present application. As shown in FIG. 3 , before step S22, the method further includes:

Step S31: The wind noise processing device transforms the first digital signal to obtain a second transformed domain spectrum.

Correspondingly, step S22 includes:

Step S32: The wind noise processing device performs spectrum separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

Wherein, the transformation performed by the wind noise processing device on the first digital signal may be discrete Fourier transform (Discrete Fourier Transform (Discrete Fourier Transform, DFT), discrete cosine transform (DCT for Discrete Cosine Transform, DCT), short-time Fourier transform (Discrete Fourier Transform, DFT), Lie transform, etc., which are not limited in this application.

For example, the first digital signal is transformed by the following transformation method to obtain the second transformed domain spectrum, and the wind noise processing device generates a vector with a frame length of N from the first digital signal according to the inter-frame interval L, where L is a positive number and N is Integer greater than 1. A windowed discrete Fourier transform is applied to the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal includes N/2+1 elements. Specifically, the wind noise processing device forms any one of the first digital signals x _c (t), c=1, 2, . The Fourier transform yields the second transform domain spectrum X _c [k] _n with N/2+1 elements:

Among them, j is an imaginary unit, and the value range of N is int[0.005fs]<=N<=int[fs], for example, N=int[0.032fs], and int[] is an integer operation. The value range of L is int[0.005fs]<=L<=int[fs], and L<N, and the typical value is L=int[0.016fs]. where h _ana [l],l=1,2,…,N is the analysis window function of N points, h _syn [l],l=1,2,…,N is the synthesis window function of N points, they satisfy the following conditions:

N=L _z +2L _t +L _O , L=L _t +L _O , where L _z and L _O are non-negative integers, and L _{t is} a non-zero integer.

h _ana [l]=h _syn [l]=0, l=1,...,L _z , if L _z is not 0.

h _ana [l]=h _syn [l]=1, l=L _z +L _t +1, ..., L _z +L _t +L _O , if L _z is not 0.

_hana [Lz+l] _{= hana} [N+1-l], l=1,2,..., _Lt .

h _syn [ _Lz +l]= _hsyn [N+1-l],l=1,2,..., _Lt .

h _ana [L _z +l]h _syn [L _z +l]+h _ana [L _z +L _t +L _O +l]h _syn [L _z +L _t +L _O +l]=1,

l=1,2,..., _Lt .

Further, the wind noise processing device performs spectrum separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

典型值为其中min()是取最小值操作。这种情况下，该第一信号变换域谱为低频信号变换域谱，第二信号变换域谱为高频信号变换域谱。In an optional manner, the wind noise processing apparatus may form the first signal transform domain spectrum corresponding to the second transform domain spectrum by the first k _L +1 elements among the N/2+1 elements included in the second transform domain spectrum, and The second signal transform domain spectrum corresponding to the second transform domain spectrum is composed of the last k _H elements among the N/2+1 elements included in the second transform domain spectrum, where k _L +k _H =N/2. where k _L is determined by N and the frequency fs of the first digital signal. E.g:

Typical value is where min() is the minimum value operation. In this case, the first signal transform domain spectrum is a low frequency signal transform domain spectrum, and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

Specifically, performing spectral separation operation on the K second transform domain spectra to obtain K high-frequency transform domain spectra X _H1 [k] _n ,...,X _HK [k] _n , k=1,2,...,k _H and K low-frequency transform domain spectra X _L1 [k] _n ,...,X _LK [k] _n , k=1,2,...,k _L +1, the operation to obtain the low-frequency transform domain spectrum is:

X _Lc [k] _n =X _c [k] _n , k=1,2,...,k _L +1, c=1,2,...,K.

The operation to obtain the high-frequency transform domain spectrum is:

X _Hc [k] _n =X _c [k _L +1+k] _n , k=1,2,...,k _H , c=1,2,...,K.

Another optional way: the wind noise processing apparatus may form elements of odd bits among the N/2+1 elements included in the second transform domain spectrum to form the first signal transform domain spectrum corresponding to the second transform domain spectrum, and combine the first signal transform domain spectrum corresponding to the second transform domain spectrum. The even-numbered elements of the N/2+1 elements included in the two transform domain spectrum constitute the second signal transform domain spectrum corresponding to the second transform domain spectrum, where k _L +k _H =N/2.

It should be noted that how to perform spectral separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum, the present application is not limited to the above two optional manners.

Describe step S23:

Optionally, FIG. 4 is a flowchart of a multi-microphone-based wind noise processing method provided by still another embodiment of the present application. As shown in FIG. 4 , step S23 includes the following steps:

Step S41 : the wind noise processing apparatus performs normalization processing on the real part and the imaginary part of the transform domain spectrum of the first signal to obtain the normalized real part and the normalized imaginary part of the first signal transform domain spectrum.

Step S42: The wind noise processing apparatus determines the minimum value of the moduli of the K first signal transform domain spectra under all domain spectra.

Step S43: The wind noise processing device obtains the third signal transform domain spectrum according to the normalized real part, the normalized imaginary part, and the minimum value of the modulus of the K first signal transform domain spectra under each domain spectrum.

Specifically, the normalized real part X _Rc [k] _n and the normalized imaginary part X _Ic [k] _n corresponding to the first signal transform domain spectrum are obtained, which satisfy the following conditions:

k=1,2,...,k _L +1, c=1,2,...,K

Where real() is the real part operation of complex numbers, imag() is the imaginary part operation of complex numbers, and abs() is the absolute value operation. Secondly, the wind noise processing device obtains the minimum absolute value of the real part and the minimum absolute value of the imaginary part of each spectrum number k of the K first signal transform domain spectra:

R _L [k] _n = min{abs[real(X _L1 [k] _n ),...,abs[real(X _LK [k] _n )}

I[k] _n = min{abs[imag(X _L1 [k] _n ),...,abs[imag(X _LK [k] _n )}

k=1,2,...,k _L +1, where min() is the minimum value operation.

Finally, the wind noise processing device obtains K third signal transform domain spectra:

Describe step S24:

In an optional manner, FIG. 5 is a flowchart of a multi-microphone-based wind noise processing method provided by another embodiment of the present application. As shown in FIG. 5 , step S24 includes the following steps:

Step S51: The wind noise processing device forms the first k _L +1 elements in the first transform domain spectrum from the third signal transform domain spectrum, and forms the second signal transform domain spectrum into the last k _H elements in the first transform domain spectrum element.

Specifically, the first transform domain spectrum X' _c [k] _n is as follows:

_X'c [k] _n = _X'LC [k] _n , k=1,2,...,k _L +1,c=1,2,...,K

X' _c [k _L +1+k] _n =X _Hc [k] _n , k=1,2,...,k _H , c=1,2,...,K.

Another optional way: the wind noise processing apparatus may form elements of the third signal transform domain spectrum into odd-bit elements in the first transform domain spectrum, and form elements of the second signal transform domain spectrum into elements in the first transform domain spectrum the even-numbered elements.

It should be noted that the combination processing method of the third signal transform domain spectrum and the second signal transform domain spectrum by the wind noise processing device corresponds to the spectrum separation processing method performed on the second transform domain spectrum. The spectral separation processing method performed on the second transform domain spectrum adopts the above-mentioned first optional method, and the spectrum combining processing method performed on the third signal transform domain spectrum and the second signal transform domain spectrum also adopts the first method in the spectrum combining processing. Optional way. If the spectral separation processing method performed by the wind noise processing device on the second transform domain spectrum adopts the above-mentioned second optional method, the spectrum combining processing method performed on the third signal transform domain spectrum and the second signal transform domain also adopts the spectral combination. The second optional way in processing.

Describe step S25:

Step S25 includes: the wind noise processing apparatus performs time domain signal reconstruction processing on the first transform domain spectrum to obtain a second digital signal.

Optionally, FIG. 6 is a flowchart of a multi-microphone-based wind noise processing method provided by still another embodiment of the present application. As shown in FIG. 6 , the wind noise processing apparatus performs time domain signal reconstruction on the first transform domain spectrum. The processing to obtain the second digital signal includes the following steps:

Step S61: The wind noise processing apparatus performs repair processing on the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum.

Step S62: The wind noise processing device performs a windowed inverse discrete Fourier transform on the third transform domain spectrum to obtain a target signal in the time domain corresponding to the first transform domain spectrum.

Step S63: The wind noise processing device performs accumulation processing on the target signals in each time domain to obtain a second digital signal.

The wind noise processing device forms the first N/2 elements of the first transform domain spectrum into the first N/2 elements of the third transform domain spectrum, and combines the last N/2 elements of the first transform domain spectrum into the first N/2 elements of the third transform domain spectrum. Conjugates make up the last N/2 elements of the third transform domain spectrum.

作N点重建，得到重建的N点修复变换域谱，即第三变换域谱：X″₁[k]_n，X″₂[k]_n……X″_K[k]_n，k＝1,2,…,N，其过程为：Specifically, for the K first transform domain spectra

Perform N-point reconstruction to obtain the reconstructed N-point repaired transform domain spectrum, that is, the third transform domain spectrum: X″ ₁ [k] _n , X″ ₂ [k] _n …X″ _K [k] _n , k=1 ,2,…,N, the process is:

Among them, * represents the conjugation operation.

Further, the wind noise processing device performs a windowed inverse discrete Fourier transform on the third transform domain spectrum to obtain a target signal in the time domain corresponding to the first transform domain spectrum. The specific process is as follows:

Further, the wind noise processing device performs an overlapping and accumulation operation on d _c [l] _n to obtain a repaired L-point time-domain audio signal.

Among them, z _c [l] _n is the output buffer of overlapping accumulation, its initial value is zero, and needs to be updated after each overlapping accumulation: z _c [l] _n =d _c [L _z +L _t +L _O +l] _n , l=1,2,...,L _t .

An embodiment of the present application provides a method for processing wind noise based on multiple microphones, including: a wind noise processing device obtains a first digital signal from K microphones respectively, and separates and processes the first digital signal for each first digital signal. A first signal transform domain spectrum and a second signal transform domain spectrum are obtained. Wind noise repair processing is performed on the first signal transform domain spectrum to obtain a third signal transform domain spectrum. The transform domain spectrum of the third signal is combined with the transform domain spectrum of the second signal to obtain the first transform domain spectrum. Reconstruction processing is performed on the first transform domain spectrum to obtain a second digital signal. The wind noise processing method provided by the present application can not only reduce wind noise interference, but also will not cause the problem of signal distortion.

The effect of the above-mentioned wind noise processing method is described below based on the dual-microphone audio acquisition system: wherein the sampling frequency of the dual-microphone audio acquisition system is fs=48000Hz, N=2048, L=1024, and the analysis window function and the synthesis window function are respectively:

FIG. 7 is a signal waveform diagram of the dual microphones provided by an embodiment of the application under the condition of being interfered by wind noise. As shown in FIG. 7 , two channels of digital audio signals (that is, the above-mentioned first digital signal) obtained by the dual-microphone audio acquisition system ) was severely disturbed by wind noise, and in some time periods, the signal was digitally overloaded due to excessive interference. FIG. 8 is a signal waveform diagram of the dual microphones provided by an embodiment of the application after wind noise processing. As shown in FIG. 8 , after wind noise processing, the restored signal (that is, the above-mentioned second digital signal) ) amplitude becomes very flat and there is no overload distortion.

FIG. 9 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 90 according to an embodiment of the present application. The wind noise processing apparatus may be part or all of smart devices such as computers, tablet computers, and mobile phones. As shown in Figure 9, the wind noise processing device includes:

The obtaining module 91 is configured to obtain a first digital signal from the K microphones respectively, where K is an integer greater than 1.

The separation processing module 92 is configured to separate and process the first digital signal for each first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum.

The wind noise repair processing module 93 is configured to perform wind noise repair processing on the first signal transform domain spectrum to obtain a third signal transform domain spectrum.

The combining module 94 is configured to combine the transform domain spectrum of the third signal with the transform domain spectrum of the second signal to obtain the first transform domain spectrum.

The reconstruction processing module 95 is configured to perform reconstruction processing on the first transform domain spectrum to obtain a second digital signal.

Optionally, FIG. 10 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 100 according to an embodiment of the present application. As shown in FIG. 10 , the separation processing module 92 includes:

The transforming unit 921 is configured to transform the first digital signal to obtain a second transform domain spectrum.

The spectral separation unit 922 is configured to perform spectral separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

Optionally, the transformation unit 921 is specifically configured to: generate a vector with a frame length of N from the first digital signal according to an inter-frame interval L, where L is a positive number, and N is an integer greater than 1. A windowed discrete Fourier transform is applied to the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal includes N/2+1 elements.

Optionally, the spectral separation unit 922 is specifically configured to: form the first signal transform domain spectrum corresponding to the second transform domain spectrum by the first k _L +1 elements in the N/2+1 elements included in the second transform domain spectrum, The second signal transform domain spectrum corresponding to the second transform domain spectrum is composed of the last k _H elements among the N/2+1 elements included in the second transform domain spectrum, where k _L +k _H =N/2.

Optionally, k _L is determined by N and the frequency fs of the first digital signal.

Optionally, the first signal transform domain spectrum is a low frequency signal transform domain spectrum, and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

Optionally, FIG. 11 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 110 according to an embodiment of the present application. As shown in FIG. 11 , the wind noise restoration processing module 93 includes:

The normalization processing unit 931 is configured to perform normalization processing on the real part and the imaginary part of the transform domain spectrum of the first signal to obtain the normalized real part and the normalized imaginary part of the first signal transform domain spectrum.

The determining unit 932 is configured to determine the minimum value of the moduli of the K first signal transform domain spectra under all domain spectra.

The processing unit 933 is configured to obtain a third signal transform domain spectrum according to the normalized real part, the normalized imaginary part, and the minimum value of the modulus of the K first signal transform domain spectra under each domain spectrum.

Optionally, the determining unit 932 is specifically configured to: determine the minimum value of the sum of the real part and the imaginary part of the K first signal transformation frequency domains in all domain spectra.

Optionally, the merging module 94 is specifically configured to: form the third signal transform domain spectrum into the first k _L +1 elements in the first transform domain spectrum, and form the second signal transform domain spectrum into the first transform domain spectrum. last k _H elements.

Optionally, the reconstruction processing module 95 is specifically configured to: perform time domain signal reconstruction processing on the first transform domain spectrum to obtain a second digital signal.

Optionally, FIG. 12 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 120 according to an embodiment of the present application. As shown in FIG. 12 , the reconstruction processing module 95 includes:

The repair processing unit 951 is configured to perform repair processing on the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum.

The inverse discrete Fourier transform unit 952 is configured to perform a windowed inverse discrete Fourier transform on the third transform domain spectrum to obtain a target signal in the time domain corresponding to the first transform domain spectrum.

The accumulation processing unit 953 is configured to perform accumulation processing on the target signals in each time domain to obtain a second digital signal.

Optionally, the repair processing unit 951 is specifically configured to: combine the first N/2 elements in the first transform domain spectrum into the first N/2 elements of the third transform domain spectrum, and combine the last N/2 elements in the first transform domain spectrum. The conjugation of N/2 elements constitutes the last N/2 elements of the third transform domain spectrum.

The wind noise processing device provided in the present application can be used to execute the above-mentioned wind noise processing method, the content and effect of which can be referred to the method section, which will not be described in this application.

FIG. 13 is a schematic diagram of a multi-microphone-based wind noise processing apparatus 130 according to an embodiment of the present application. As shown in FIG. 13 , the wind noise processing apparatus 130 includes: a processing unit 131 , K first filters 132 , The processing units 131 are respectively connected to the K first filters 132 .

The processing unit 131 is configured to obtain a first digital signal from the K microphones respectively, where K is an integer greater than 1. For each first digital signal, the first digital signal is separated and processed to obtain a first signal transform domain spectrum and a second signal transform domain spectrum. Wind noise repair processing is performed on the first signal transform domain spectrum to obtain a third signal transform domain spectrum. The transform domain spectrum of the third signal is combined with the transform domain spectrum of the second signal to obtain the first transform domain spectrum.

The first filter 132 is used for: reconstructing the first transform domain spectrum to obtain a second digital signal.

Optionally, the wind noise processing apparatus 130 further includes: K second filters 133 , wherein the processing unit 131 is respectively connected to the K second filters 133 . The second filter 133 is used for: transforming the first digital signal to obtain a second transform domain spectrum before performing separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum. Correspondingly, the processing unit 131 is specifically configured to: perform spectral separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

Optionally, the second filter 133 is specifically configured to: generate a vector with a frame length of N from the first digital signal according to an inter-frame interval L, where L is a positive number, and N is an integer greater than 1. A windowed discrete Fourier transform is applied to the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal includes N/2+1 elements.

Optionally, the processing unit 131 is specifically configured to: form the first signal transform domain spectrum corresponding to the second transform domain spectrum by the first k _L +1 elements among the N/2+1 elements included in the second transform domain spectrum, and The second signal transform domain spectrum corresponding to the second transform domain spectrum is composed of the last k _H elements among the N/2+1 elements included in the second transform domain spectrum, where k _L +k _H =N/2.

Optionally, k _L is determined by N and the frequency fs of the first digital signal.

Optionally, the first signal transform domain spectrum is a low frequency signal transform domain spectrum, and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

Optionally, the processing unit 131 is specifically configured to: normalize the real part and the imaginary part of the transform domain spectrum of the first signal to obtain the normalized real part and the normalized imaginary part of the transform domain spectrum of the first signal. Determine the minimum value of the modulus of the K first signal transform domain spectra under all domain spectra. According to the normalized real part, the normalized imaginary part, and the minimum value of the modulus of the K first signal transform domain spectra under each domain spectrum, the third signal transform domain spectrum is obtained.

Optionally, the processing unit 131 is specifically configured to: determine the minimum value of the sum of the real part and the imaginary part of the K first signal transformation frequency domains in all domain spectra.

Optionally, the processing unit 131 is specifically configured to: form the third signal transform domain spectrum into the first k _L +1 elements in the first transform domain spectrum, and form the second signal transform domain spectrum into the first transform domain spectrum. last k _H elements.

Optionally, the first filter 132 is specifically configured to: perform time-domain signal reconstruction processing on the first transform-domain spectrum to obtain a second digital signal.

Optionally, the first filter 132 is specifically configured to: perform repair processing on the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum. The windowed inverse discrete Fourier transform is performed on the third transform domain spectrum to obtain the target signal in the time domain corresponding to the first transform domain spectrum. Accumulate the target signals in each time domain to obtain a second digital signal.

Optionally, the first filter 132 is specifically configured to: form the first N/2 elements in the first transform domain spectrum into the first N/2 elements of the third transform domain spectrum, and combine the first N/2 elements in the first transform domain spectrum. The conjugation of the last N/2 elements constitutes the last N/2 elements of the third transform domain spectrum.

The wind noise processing device provided in the present application can be used to execute the above-mentioned wind noise processing method, the content and effect of which can be referred to the method section, which will not be described in this application.

FIG. 14 is a schematic diagram of a multi-microphone-based wind noise processing system 140 according to an embodiment of the present application. As shown in FIG. 14 , the system 140 includes a wind noise processing device 141 and K microphones 142 . The K microphones 142 are connected to the wind noise processing device 141 .

Wherein, the wind noise processing device includes:

The obtaining module is used to obtain a first digital signal from the K microphones respectively, where K is an integer greater than 1.

The separation processing module is configured to separate and process the first digital signal for each first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum.

The wind noise repair processing module is used for performing wind noise repair processing on the first signal transform domain spectrum to obtain the third signal transform domain spectrum.

The combining module is used for combining the transform domain spectrum of the third signal with the transform domain spectrum of the second signal to obtain the first transform domain spectrum.

The reconstruction processing module is used for reconstructing the first transform domain spectrum to obtain a second digital signal.

Optionally, the separation processing module includes:

The transforming unit is used for transforming the first digital signal to obtain the second transform domain spectrum.

The spectral separation unit is configured to perform spectral separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

Optionally, the transformation unit is specifically configured to: generate a vector with a frame length of N from the first digital signal according to an inter-frame interval L, where L is a positive number, and N is an integer greater than 1. A windowed discrete Fourier transform is applied to the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal includes N/2+1 elements.

Optionally, the spectrum separation unit is specifically configured to: form the first signal transform domain spectrum corresponding to the second transform domain spectrum by the first k _L +1 elements in the N/2+1 elements included in the second transform domain spectrum, and The second signal transform domain spectrum corresponding to the second transform domain spectrum is composed of the last k _H elements among the N/2+1 elements included in the second transform domain spectrum, where k _L +k _H =N/2.

Optionally, k _L is determined by N and the frequency fs of the first digital signal.

Optionally, the first signal transform domain spectrum is a low frequency signal transform domain spectrum, and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

Optionally, the wind noise restoration processing module includes:

The normalization processing unit is configured to perform normalization processing on the real part and the imaginary part of the transform domain spectrum of the first signal to obtain the normalized real part and the normalized imaginary part of the first signal transform domain spectrum.

The determining unit is configured to determine the minimum value of the moduli of the K first signal transform domain spectra under all domain spectra.

The processing unit is configured to obtain the third signal transform domain spectrum according to the normalized real part, the normalized imaginary part, and the minimum value of the modulus of the K first signal transform domain spectra under each domain spectrum.

Optionally, the determining unit is specifically configured to: determine the minimum value of the sum of the real part and the imaginary part of the K first signal transform frequency domains in all domain spectra.

Optionally, the merging module is specifically used for: composing the third signal transform domain spectrum into the first k _L +1 elements in the first transform domain spectrum, and forming the second signal transform domain spectrum into the last element in the first transform domain spectrum. k _H elements.

Optionally, the reconstruction processing module is specifically configured to: perform time domain signal reconstruction processing on the first transform domain spectrum to obtain the second digital signal.

Optionally, the reconstruction processing module includes:

The repair processing unit is configured to perform repair processing on the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum.

The inverse discrete Fourier transform unit is used to perform windowed inverse discrete Fourier transform on the third transform domain spectrum to obtain the target signal in the time domain corresponding to the first transform domain spectrum.

The accumulation processing unit is configured to perform accumulation processing on the target signals in each time domain to obtain a second digital signal.

Optionally, the repair processing unit is specifically configured to: combine the first N/2 elements in the first transform domain spectrum into the first N/2 elements of the third transform domain spectrum, and combine the last N/2 elements in the first transform domain spectrum. The conjugation of /2 elements forms the last N/2 elements of the third transform domain spectrum.

The wind noise processing system provided in the present application includes a wind noise processing device, which can be used to execute the above-mentioned wind noise processing method, the content and effect of which can be referred to the method section, which is not described in this application.

FIG. 15 is a schematic diagram of a multi-microphone-based wind noise processing system 150 according to an embodiment of the present application. As shown in FIG. 15 , the system 150 includes a wind noise processing device 151 and K microphones 152 . The K microphones 152 are connected to the wind noise processing device 151 .

Wherein, the wind noise processing device includes:

A processing unit and K first filters, wherein the processing unit is respectively connected with the K first filters.

The processing unit is configured to: obtain a first digital signal from the K microphones respectively, where K is an integer greater than 1. For each first digital signal, the first digital signal is separated and processed to obtain a first signal transform domain spectrum and a second signal transform domain spectrum. Wind noise repair processing is performed on the first signal transform domain spectrum to obtain a third signal transform domain spectrum. The transform domain spectrum of the third signal is combined with the transform domain spectrum of the second signal to obtain the first transform domain spectrum.

The first filter is used for: reconstructing the first transform domain spectrum to obtain a second digital signal.

Optionally, the wind noise processing apparatus further includes: K second filters, wherein the processing units are respectively connected to the K second filters. The second filter is used for: transforming the first digital signal to obtain a second transform domain spectrum before performing separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum. Correspondingly, the processing unit is specifically configured to: perform spectral separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

Optionally, the second filter is specifically configured to: generate a vector with a frame length of N from the first digital signal according to an inter-frame interval L, where L is a positive number, and N is an integer greater than 1. A windowed discrete Fourier transform is applied to the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal includes N/2+1 elements.

Optionally, the processing unit is specifically configured to: form the first signal transform domain spectrum corresponding to the second transform domain spectrum by the first k _L +1 elements in the N/2+1 elements included in the second transform domain spectrum, and combine The last k _H elements among the N/2+1 elements included in the second transform domain spectrum constitute the second signal transform domain spectrum corresponding to the second transform domain spectrum, where k _L +k _H =N/2.

Optionally, k _L is determined by N and the frequency fs of the first digital signal.

Optionally, the first signal transform domain spectrum is a low frequency signal transform domain spectrum, and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

Optionally, the processing unit is specifically configured to: normalize the real part and the imaginary part of the transform domain spectrum of the first signal to obtain the normalized real part and the normalized imaginary part of the transform domain spectrum of the first signal. Determine the minimum value of the modulus of the K first signal transform domain spectra under all domain spectra. According to the normalized real part, the normalized imaginary part, and the minimum value of the modulus of the K first signal transform domain spectra under each domain spectrum, the third signal transform domain spectrum is obtained.

Optionally, the processing unit is specifically configured to: determine the minimum value of the sum of the real part and the imaginary part of the K first signal transform frequency domains in all domain spectra.

Optionally, the processing unit is specifically configured to: form the third signal transform domain spectrum into the first k _L +1 elements in the first transform domain spectrum, and form the second signal transform domain spectrum into the last one in the first transform domain spectrum. k _H elements.

Optionally, the first filter is specifically configured to: perform time-domain signal reconstruction processing on the first transform-domain spectrum to obtain a second digital signal.

Optionally, the first filter is specifically configured to: perform repair processing on the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum. The windowed inverse discrete Fourier transform is performed on the third transform domain spectrum to obtain the target signal in the time domain corresponding to the first transform domain spectrum. Accumulate the target signals in each time domain to obtain a second digital signal.

Optionally, the first filter is specifically used to: form the first N/2 elements in the first transform domain spectrum into the first N/2 elements of the third transform domain spectrum, and combine the last N/2 elements in the first transform domain spectrum. The conjugation of N/2 elements constitutes the last N/2 elements of the third transform domain spectrum.

The wind noise processing system provided in the present application includes a wind noise processing device, which can be used to execute the above-mentioned wind noise processing method, the content and effect of which can be referred to the method section, which is not described in this application.

It should be noted that the processor involved in this application may be a motor controller MCU (Motor control unit, MCU for short), a central processing unit (Central Processing Unit, CPU for short), or other general-purpose processors and digital signal processors. (Digital Signal Processor, referred to as: DSP), application specific integrated circuit (Application Specific Integrated Circuit, referred to as: ASIC) and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the methods disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

The present application also provides a computer storage medium, including: computer instructions, where the computer instructions are used to implement the above-mentioned multi-microphone-based wind noise processing method, the content and effect of which can be referred to the method section, which will not be described in this application.

The present application also provides a computer program product, comprising: computer instructions, where the computer instructions are used to implement the above-mentioned multi-microphone-based wind noise processing method, the content and effect of which can be referred to the method section, which will not be described in this application.

Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments may be completed by program instructions related to hardware. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps including the above method embodiments are executed; and the foregoing storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features thereof can be equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present application. scope.

Claims (39)

1. A multi-microphone based wind noise processing method is characterized by comprising the following steps:

respectively acquiring a first digital signal from K microphones, wherein K is an integer greater than 1;

for each first digital signal, performing separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum;

wind noise restoration processing is carried out on the first signal transform domain spectrum to obtain a third signal transform domain spectrum;

combining the third signal transform domain spectrum and the second signal transform domain spectrum to obtain a first transform domain spectrum;

and reconstructing the first transform domain spectrum to obtain a second digital signal.

2. The method of claim 1, wherein before performing the separation process on each first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum, further comprising:

transforming the first digital signal to obtain a second transform domain spectrum;

correspondingly, the separating the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum includes:

and carrying out spectrum separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

3. The method of claim 2, wherein transforming the first digital signal to obtain a second transform domain spectrum comprises:

generating a vector with the frame length of N by the first digital signal according to an interframe interval L, wherein L is a positive number, and N is an integer greater than 1;

and performing windowed discrete Fourier transform on the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal comprises N/2+1 elements.

4. The method of claim 2, wherein said spectrally separating said second transform-domain spectrum to obtain said first signal transform-domain spectrum and said second signal transform-domain spectrum comprises:

the first k of the N/2+1 elements comprised by the second transform domain spectrum _LThe +1 elements form a first signal transform domain spectrum corresponding to the second transform domain spectrum, and the second transform domain spectrum comprises the post k of N/2+1 elements _HEach element constituting a second signal transform domain spectrum corresponding to said second transform domain spectrum, wherein k _L+k _H＝N/2。

5. The method of claim 4,

k is _LIs determined by said N and the frequency fs of said first digital signal.

6. The method according to any of claims 2-4, wherein the first signal transform domain spectrum is a low frequency signal transform domain spectrum and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

7. The method according to any one of claims 1 to 5, wherein the performing a wind noise restoration process on the first signal transform domain spectrum to obtain a third signal transform domain spectrum comprises:

normalizing the real part and the imaginary part of the first signal transform domain spectrum to obtain a normalized real part and a normalized imaginary part of the first signal transform domain spectrum;

determining the minimum value of the modulus of the K first signal transformation domain spectrums under all the domain spectrums;

and obtaining the third signal transform domain spectrum according to the normalized real part, the normalized imaginary part and the minimum value of the modulus of the K first signal transform domain spectrums under each domain spectrum.

8. The method of claim 7, wherein determining the minimum of the modulus of the K first signal transform domain spectra under all domain spectra comprises:

determining a minimum of a sum of real and imaginary parts of the K first signal transform frequency domains at all domain spectra.

9. The method according to any of claims 1-5, wherein said combining said third signal transform domain spectrum with said second signal transform domain spectrum to obtain a first transform domain spectrum comprises:

forming the third signal transform domain spectrum into a top k in the first transform domain spectrum _L+1 elements, and composing the second signal transform domain spectrum into a k-last in the first transform domain spectrum _HAnd (4) each element.

10. The method according to any one of claims 1-5, wherein said reconstructing the first transform domain spectrum to obtain a second digital signal comprises:

and performing time domain signal reconstruction processing on the first transform domain spectrum to obtain the second digital signal.

11. The method of claim 10, wherein the performing a time-domain signal reconstruction process on the first transform-domain spectrum to obtain the second digital signal comprises:

repairing the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum;

performing windowing inverse discrete Fourier transform on the third transform domain spectrum to obtain a target signal on a time domain corresponding to the first transform domain spectrum;

and accumulating the target signals in each time domain to obtain the second digital signal.

12. The method according to claim 11, wherein the performing the repair process on the first transform-domain spectrum to obtain a third transform-domain spectrum corresponding to the first transform-domain spectrum comprises:

forming first N/2 elements of the first transform-domain spectrum into first N/2 elements of the third transform-domain spectrum, and forming conjugates of last N/2 elements of the first transform-domain spectrum into last N/2 elements of the third transform-domain spectrum.

13. A multi-microphone based wind noise processing apparatus, comprising:

the acquisition module is used for respectively acquiring a first digital signal from K microphones, wherein K is an integer greater than 1;

the separation processing module is used for separating the first digital signals to obtain a first signal transform domain spectrum and a second signal transform domain spectrum aiming at each first digital signal;

the wind noise restoration processing module is used for performing wind noise restoration processing on the first signal transform domain spectrum to obtain a third signal transform domain spectrum;

a merging module, configured to merge the third signal transform domain spectrum and the second signal transform domain spectrum to obtain a first transform domain spectrum;

and the reconstruction processing module is used for reconstructing the first transform domain spectrum to obtain a second digital signal.

14. The apparatus of claim 13, wherein the separation processing module comprises:

the transformation unit is used for transforming the first digital signal to obtain a second transform domain spectrum;

and the spectrum separation unit is used for performing spectrum separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

15. The apparatus according to claim 14, wherein the transformation unit is specifically configured to:

generating a vector with the frame length of N by the first digital signal according to an interframe interval L, wherein L is a positive number, and N is an integer greater than 1;

and performing windowed discrete Fourier transform on the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal comprises N/2+1 elements.

16. The apparatus according to claim 14, wherein the spectral separation unit is specifically configured to:

the first k of the N/2+1 elements comprised by the second transform domain spectrum _LThe +1 elements form a first signal transform domain spectrum corresponding to the second transform domain spectrum, and the second transform domain spectrum comprises the post k of N/2+1 elements _HEach element constituting a second signal transform domain spectrum corresponding to said second transform domain spectrum, wherein k _L+k _H＝N/2。

17. The apparatus of claim 16,

the kL is determined by the N and the frequency fs of the first digital signal.

18. The apparatus of any of claims 15-17, wherein the first signal transform domain spectrum is a low frequency signal transform domain spectrum and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

19. The apparatus according to any one of claims 13-17, wherein the wind noise restoration processing module comprises:

the normalization processing unit is used for performing normalization processing on the real part and the imaginary part of the first signal transform domain spectrum to obtain a normalized real part and a normalized imaginary part of the first signal transform domain spectrum;

a determining unit for determining a minimum of the modes of the K first signal transform domain spectra under all domain spectra;

and the processing unit is used for obtaining the third signal transform domain spectrum according to the normalized real part, the normalized imaginary part and the minimum value of the modulus of the K first signal transform domain spectrums under each domain spectrum.

20. The apparatus according to claim 19, wherein the determining unit is specifically configured to:

determining a minimum of a sum of real and imaginary parts of the K first signal transform frequency domains at all domain spectra.

21. The apparatus according to any one of claims 13 to 17, wherein the merging module is specifically configured to:

and forming the third signal transform domain spectrum into the first kL +1 elements in the first transform domain spectrum, and forming the second signal transform domain spectrum into the second kH elements in the first transform domain spectrum.

22. The apparatus according to any one of claims 13-17, wherein the reconstruction processing module is specifically configured to:

and performing time domain signal reconstruction processing on the first transform domain spectrum to obtain the second digital signal.

23. The apparatus of claim 22, wherein the reconstruction processing module comprises:

the restoration processing unit is used for restoring the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum;

the inverse discrete Fourier transform unit is used for performing windowing inverse discrete Fourier transform on the third transform domain spectrum to obtain a target signal on a time domain corresponding to the first transform domain spectrum;

and the accumulation processing unit is used for carrying out accumulation processing on the target signals in each time domain to obtain the second digital signals.

24. The apparatus according to claim 23, wherein the repair processing unit is specifically configured to:

forming first N/2 elements of the first transform-domain spectrum into first N/2 elements of the third transform-domain spectrum, and forming conjugates of last N/2 elements of the first transform-domain spectrum into last N/2 elements of the third transform-domain spectrum.

25. A multi-microphone based wind noise processing apparatus, comprising: the filter comprises a processing unit and K first filters, wherein the processing unit is respectively connected with the K first filters;

the processing unit is configured to:

respectively acquiring a first digital signal from K microphones, wherein K is an integer greater than 1;

for each first digital signal, performing separation processing on the first digital signal to obtain a first signal transform domain spectrum and a second signal transform domain spectrum;

wind noise restoration processing is carried out on the first signal transform domain spectrum to obtain a third signal transform domain spectrum;

combining the third signal transform domain spectrum and the second signal transform domain spectrum to obtain a first transform domain spectrum;

the first filter is to:

and reconstructing the first transform domain spectrum to obtain a second digital signal.

26. The apparatus of claim 25, further comprising: the processing unit is respectively connected with the K second filters;

the second filter is to: before the first digital signal is subjected to separation processing to obtain a first signal transform domain spectrum and a second signal transform domain spectrum, the first digital signal is transformed to obtain a second transform domain spectrum;

correspondingly, the processing unit is specifically configured to:

and carrying out spectrum separation processing on the second transform domain spectrum to obtain the first signal transform domain spectrum and the second signal transform domain spectrum.

27. The apparatus of claim 26, wherein the second filter is specifically configured to:

generating a vector with the frame length of N by the first digital signal according to an interframe interval L, wherein L is a positive number, and N is an integer greater than 1;

and performing windowed discrete Fourier transform on the vector to obtain a second transform domain spectrum corresponding to the first digital signal, wherein the second transform domain spectrum corresponding to the first digital signal comprises N/2+1 elements.

28. The apparatus according to claim 26, wherein the processing unit is specifically configured to: the first k of the N/2+1 elements comprised by the second transform domain spectrum _LThe +1 elements form a first signal transform domain spectrum corresponding to the second transform domain spectrum, and the second transform domain spectrum comprises the post k of N/2+1 elements _HEach element constituting a second signal transform domain spectrum corresponding to said second transform domain spectrum, wherein k _L+k _H＝N/2。

29. The apparatus of claim 28 wherein kL is determined by said N and a frequency fs of said first digital signal.

30. The apparatus of any of claims 26-29, wherein the first signal transform domain spectrum is a low frequency signal transform domain spectrum and the second signal transform domain spectrum is a high frequency signal transform domain spectrum.

31. The apparatus according to any one of claims 25 to 29, wherein the processing unit is specifically configured to:

normalizing the real part and the imaginary part of the first signal transform domain spectrum to obtain a normalized real part and a normalized imaginary part of the first signal transform domain spectrum;

determining the minimum value of the modulus of the K first signal transformation domain spectrums under all the domain spectrums;

and obtaining the third signal transform domain spectrum according to the normalized real part, the normalized imaginary part and the minimum value of the modulus of the K first signal transform domain spectrums under each domain spectrum.

32. The apparatus according to claim 31, wherein the processing unit is specifically configured to:

determining a minimum of a sum of real and imaginary parts of the K first signal transform frequency domains at all domain spectra.

33. The apparatus according to any one of claims 25 to 29, wherein the processing unit is specifically configured to:

and forming the third signal transform domain spectrum into the first kL +1 elements in the first transform domain spectrum, and forming the second signal transform domain spectrum into the second kH elements in the first transform domain spectrum.

34. The apparatus according to any of claims 25-29, wherein the first filter is specifically configured to:

and performing time domain signal reconstruction processing on the first transform domain spectrum to obtain the second digital signal.

35. The apparatus of claim 34, wherein the first filter is specifically configured to:

repairing the first transform domain spectrum to obtain a third transform domain spectrum corresponding to the first transform domain spectrum;

performing windowing inverse discrete Fourier transform on the third transform domain spectrum to obtain a target signal on a time domain corresponding to the first transform domain spectrum;

and accumulating the target signals in each time domain to obtain the second digital signal.

36. The apparatus of claim 35, wherein the first filter is specifically configured to:

forming first N/2 elements of the first transform-domain spectrum into first N/2 elements of the third transform-domain spectrum, and forming conjugates of last N/2 elements of the first transform-domain spectrum into last N/2 elements of the third transform-domain spectrum.

37. A multi-microphone based wind noise processing system, comprising: a wind noise processing apparatus as claimed in any of claims 13 to 24 and K microphones; wherein the K microphones are connected with the wind noise processing device.

38. A multi-microphone based wind noise processing system, comprising: a wind noise processing apparatus as claimed in any of claims 25 to 36 and K microphones; wherein the K microphones are connected with the wind noise processing device.

39. A computer storage medium, comprising: computer instructions for implementing a multi-microphone based wind noise processing method according to any of claims 1-12.

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