CN109313909A - Assess method, unit and the system of microphone array consistency - Google Patents
Assess method, unit and the system of microphone array consistency Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
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Abstract
The embodiment of the present application provides a kind of method, unit and system for assessing microphone array consistency, the consistency in microphone array between different microphones can be assessed, to instruct the calibration of microphone array and the robustness of assessment multichannel enhancing algorithm according to compliance evaluation result, user experience is promoted.This method comprises: obtaining N number of audio signal that N number of microphone acquires respectively, which constitutes microphone array, N >=2；According to N number of audio signal, each microphone in N number of microphone in addition to reference microphone and phase spectrum difference and/or power spectrum difference between the reference microphone are determined, which is any one microphone in N number of microphone；According to each microphone in N number of microphone in addition to the reference microphone and phase spectrum difference and/or power spectrum difference between the reference microphone, compliance evaluation is carried out to N number of microphone.
Description
Technical field
This application involves speech communications and speech-sound intelligent interaction field, and more particularly, to assessment microphone array
Method, unit and the system of consistency.
Background technique
In speech communication application, speech enhancement technique can be improved the auditory perception of people, improve understanding for speech communication
Degree, in speech-sound intelligent interactive application, speech enhancement technique can be improved the accuracy rate of speech recognition, promote user experience, because
This speech enhancement technique is either crucial in traditional speech communication or interactive voice.Speech enhancement technique point
Enhancing technology and multicenter voice for single-channel voice enhances technology, wherein single-channel voice enhancing technology can eliminate stable state
Noise cannot eliminate nonstationary noise, and signal is using speech damage as cost than improving, and signal-to-noise ratio improves more, voice damage
Hurt bigger；Multicenter voice enhances technology and acquires multiple signals using microphone array, utilizes the phase between multi-microphone signal
Position information and coherence messages eliminate noise, can eliminate nonstationary noise, and smaller to speech damage.
In multicenter voice enhancing technology, the consistency in microphone array between different microphones directly affects algorithm
Performance, existing scheme propose the innovatory algorithm of multichannel enhancing technology, increase the robustness of algorithm, while between microphone
Coherence request reduce, however, the consistency between microphone still will affect algorithm performance when very low, to affect use
Family experience.
Summary of the invention
The application provides a kind of method, unit and system for assessing microphone array consistency, can assess Mike
Consistency in wind array between different microphones, to instruct the calibration of microphone array according to compliance evaluation result and comment
The robustness for estimating multichannel enhancing algorithm, promotes user experience.
In a first aspect, providing a kind of method for assessing microphone array consistency, comprising:
N number of audio signal that N number of microphone acquires respectively is obtained, which constitutes microphone array, N >=2；
According to N number of audio signal, each microphone and the ginseng in N number of microphone in addition to reference microphone are determined
The phase spectrum difference and/or power spectrum difference between microphone are examined, which is any one in N number of microphone
Microphone；
According to each microphone in N number of microphone in addition to the reference microphone and the phase between the reference microphone
Position spectral difference value and/or power spectrum difference carry out compliance evaluation to N number of microphone.
It should be noted that carrying out compliance evaluation to N number of microphone, it can be used for instructing the wheat in microphone array
The distribution of gram wind, or guidance redesign the microphone distribution in microphone array, or guidance redesigns microphone array
Column, or the robustness of assessment multichannel enhancing algorithm.
For example, when assessment result shows that the consistency of microphone 1 and microphone 2 is poor, can instruct adjustment microphone 1 or
Distribution of the person's microphone 2 in microphone array can either be instructed to redesign microphone 1 or microphone 2.
In another example adjustment wheat can be instructed when assessment result shows that the consistency of microphone 1 and multiple microphones is all poor
Gram distribution of the wind 1 in microphone array can perhaps be instructed to redesign microphone 1 or can instruct to redesign wheat
Gram wind array.
In the embodiment of the present application, the N number of audio signal acquired respectively according to N number of microphone, determine each microphone with
Phase spectrum difference and/or power spectrum difference between reference microphone are eliminated to carry out compliance evaluation to N number of microphone
Influence of the consistency to multicenter voice enhancing algorithm between microphone, promotes user experience.
In some possible implementations, each wheat according in N number of microphone in addition to reference microphone
Phase spectrum difference gram between wind and the reference microphone carries out compliance evaluation to N number of microphone, comprising:
According to each microphone in N number of microphone in addition to the reference microphone and the phase between the reference microphone
Position spectral difference value, assesses the phase equalization between corresponding microphone and the reference microphone.
It should be noted that the phase spectrum difference between two microphones is smaller, the phase between the two microphones is indicated
Bit integrity is better.
For example, the phase spectrum difference between microphone 1 and reference microphone is A, A is smaller, indicates microphone 1 and refers to wheat
Phase equalization between gram wind is better.
It is alternatively possible to a threshold value be arranged, if the phase spectrum difference between two microphones is less than this threshold value, table
Show that the phase equalization between the two microphones meets design requirement, the consistency between the two microphones is to multichannel language
Sound enhancing algorithm influence can ignore or the two microphones between consistency to multicenter voice enhancing algorithm do not have
It influences.
It should be noted that above-mentioned threshold value can enhance algorithm flexible configuration according to different multicenter voices.
In some possible implementations, this method further include:
The each microphone and the reference microphone to sound in N number of microphone in addition to the reference microphone are measured respectively
The range difference in source；
According to measured range difference, each Mike in N number of microphone in addition to the reference microphone is calculated separately
Fixed skew between wind and the reference microphone；
According to each microphone in N number of microphone in addition to the reference microphone and consolidating between the reference microphone
Phase bit is poor, calibrates its corresponding phase spectrum difference respectively.
For example, the fixed skew between microphone 1 and reference microphone is A, between microphone 1 and reference microphone
Phase spectrum difference is B, and after calibration, the phase spectrum difference between microphone 1 and reference microphone is C, at this point, C=B-A.
In some possible implementations, the distance according to measured by is calculated separately to remove in N number of microphone and is somebody's turn to do
The fixed skew between each microphone and the reference microphone except reference microphone, comprising:
According to formulaIt calculates separately in N number of microphone in addition to the reference microphone
Fixed skew between each microphone and the reference microphone,
Wherein, Yi(ω) indicates the frequency spectrum of i-th of microphone, Y1(ω) indicates that the frequency spectrum of reference microphone, ω indicate frequency
Rate, diIndicate the range difference of i-th of microphone and reference microphone to sound source, the c expression velocity of sound, 2 π ω di/ c indicates i-th of Mike
Fixed skew between wind and reference microphone.
In some possible implementations, each wheat according in N number of microphone in addition to reference microphone
Phase spectrum difference gram between wind and the reference microphone carries out compliance evaluation to N number of microphone, comprising:
According to each microphone in N number of microphone in addition to the reference microphone and the function between the reference microphone
Rate spectral difference value assesses the amplitude coincidence between corresponding microphone and the reference microphone.
It should be noted that the power spectrum difference between two microphones is smaller, the width between the two microphones is indicated
It is better to spend consistency.
For example, the power spectrum difference between microphone 1 and reference microphone is A, A is smaller, indicates microphone 1 and refers to wheat
Amplitude coincidence between gram wind is better.
It is alternatively possible to a threshold value be arranged, if the power spectrum difference between two microphones is less than this threshold value, table
Show that the amplitude coincidence between the two microphones meets design requirement, the consistency between the two microphones is to multichannel language
Sound enhancing algorithm influence can ignore or the two microphones between consistency to multicenter voice enhancing algorithm do not have
It influences.
It should be noted that above-mentioned threshold value can enhance algorithm flexible configuration according to different multicenter voices.
In some possible implementations, when carrying out phase equalization assessment, which swept in broadcasting
The signal acquired in the environment of frequency signal data.
In some possible implementations, when carrying out amplitude coincidence assessment, which is to play height
The signal acquired in the environment of this white noise data or swept-frequency signal data.
In some possible implementations, which is Linear chirp, logarithm swept-frequency signal, linear stepping
Any one in swept-frequency signal, logarithm stepping swept-frequency signal.
It is described according to N number of audio signal in some possible implementations, it determines in N number of microphone except reference
The phase spectrum difference and/or power spectrum difference between each microphone and the reference microphone except microphone, comprising:
Each audio signal in N number of audio signal is subjected to framing, obtains K signal frame of equal length, K >=2；
Windowing process is done to each signal frame in the K signal frame, obtains K windowing signal frame；
Fast Fourier transform (Fast Fourier is done to each windowing signal frame in the K windowing signal frame
Transformation, FFT) transformation, obtain K echo signal frame；
According to the corresponding K echo signal frame of each audio signal, determine in N number of microphone except this is with reference to Mike
The phase spectrum difference and/or power spectrum difference between each microphone and the reference microphone except wind.
Optionally, K indicates that each microphone collects the totalframes of signal.
It should be noted that bring truncation effect when windowing process is used to eliminate framing.It is alternatively possible to be to the K
Each signal frame in a signal frame is done plus Hamming window processing.
In some possible implementations, any two adjacent signals frame is overlapped R%, R > 0 in the K signal frame.Example
Such as, which is 25 or 50.
Optionally, signal amplitude remains unchanged after being overlapped adding window.
It should be understood that each frame signal after overlapping has the ingredient of previous frame, prevent discontinuous between two frames.
In some possible implementations, i-th of audio signal is subjected to framing, obtains K signal of equal length
Frame is write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone collects the totalframes of signal, []TIt indicates
The transposition of vector or matrix.
It is described according to the corresponding K echo signal frame of each audio signal in some possible implementations, really
Each microphone in addition to the reference microphone and the phase spectrum difference between the reference microphone in fixed N number of microphone,
Include:
According to formulaIt determines in N number of microphone in addition to the reference microphone
Each microphone and the reference microphone between phase spectrum difference,
Wherein, imag () expression takes imaginary part, and ln () expression takes natural logrithm,Indicate i-th of microphone and ginseng
The phase spectrum difference between microphone is examined,Indicate j-th of echo signal frame of reference microphone,Indicate i-th
J-th of echo signal frame of a microphone,Indicate basic frequency.
It is described according to the corresponding K echo signal frame of each audio signal in some possible implementations, really
Each microphone in addition to the reference microphone and the power spectrum difference between the reference microphone in fixed N number of microphone,
Include:
According to the corresponding K echo signal frame of each audio signal, the power spectrum of each audio signal is determined；
According to the power spectrum of each audio signal, determine in N number of microphone each of in addition to the reference microphone
Power spectrum difference between microphone and the reference microphone.
It is described according to the corresponding K echo signal frame of each audio signal in some possible implementations, really
The power spectrum of fixed each audio signal, comprising:
According to formulaThe power spectrum of each audio signal is calculated,
Wherein, Pi(ω) indicates the power spectrum of i-th of audio signal, Yi,j(ω) indicates the jth in i-th of audio signal
A echo signal frame, K indicate that each microphone receives the totalframes of signal, and ω indicates frequency.
In some possible implementations, the power spectrum according to each audio signal determines N number of microphone
In each microphone in addition to the reference microphone and the power spectrum difference between the reference microphone, comprising:
According to formula PDi(ω)=P1(ω)-Pi(ω) is calculated in N number of microphone each of in addition to reference microphone
Power spectrum difference between microphone and the reference microphone,
Wherein, PDi(ω) indicates the power spectrum difference between i-th of microphone and reference microphone, P1(ω) indicates reference
The power spectrum of microphone, Pi(ω) indicates the power spectrum of i-th of microphone.
In some possible implementations, the N number of audio signal for obtaining N number of microphone and acquiring respectively, comprising:
Determine sample frequency F of the N number of microphone when carrying out audio signal samplesWith FFT points Nfft, use loudspeaking
Device plays white Gaussian noise data or swept-frequency signal data, N number of microphone acquire N number of audio signal, wherein if this is raised
The data that sound device is played are swept-frequency signal data, and the swept-frequency signal data are equal by M+1 segment length and the signal of frequency not etc.
It constitutes,
It should be noted that FFT points NfftFor even number, generally 32,64,128 ..., 1024 etc., it counts more, fortune
The saving of calculation amount is bigger.
In some possible implementations, according to formulaCalculate the frequency of every segment signal in the M+1 segment signal
Rate, and
According to formula Si(t)=sin (2 π fiT) every segment signal in the M+1 segment signal is calculated,
Wherein, fiIndicate the frequency of the i-th segment signal, FsIndicate sample frequency, NfftIndicate FFT points, Si(t) i-th is indicated
Segment signal, and S1(t) length is the integral multiple of cycle T, T=1/f1。
In some possible implementations, the swept-frequency signal data that loudspeaker is played can be write as following vector shape
Formula:
S (t)=[S0(t),S1(t),…,SM(t)]T
Wherein, S (t) indicates the swept-frequency signal data that loudspeaker is played, Si(t) the i-th segment signal is indicated,
[ ]TIndicate the transposition of vector or matrix.
In some possible implementations, which collects N number of audio signal respectively, wherein i-th of Mike
The collected audio signal of wind is expressed as xiAnd x (t),i(t) it can be write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) the collected audio signal of i-th of microphone is indicated, K indicates that each microphone collects signal
Totalframes, []TIndicate the transposition of vector or matrix.
In some possible implementations, the N number of audio signal for obtaining N number of microphone and acquiring respectively, comprising:
N number of microphone is placed in test room, loudspeaker, N number of microphone position are configured in the test room
In the front of the loudspeaker；
It controls the loudspeaker and plays white Gaussian noise data or swept-frequency signal data, and control N number of microphone point
N number of audio signal is not acquired.
In some possible implementations, there is noise reduction room environmental in the test room, which is audio-frequency test
Special artificial mouth, and the artificial mouth is calibrated with standard microphone before the use.
In some possible implementations, white Gaussian noise data or swept-frequency signal number are played controlling the loudspeaker
According to before, this method further include:
Under quiet environment, N number of microphone is obtained in the first duration T1First audio data X of interior acquisition1(n)；
In the environment of playing white Gaussian noise data or swept-frequency signal data, N number of microphone is obtained at second
The second audio data X acquired in long T22(n)；
According to formulaSignal to Noise Ratio (SNR) is calculated, and ensures that the SNR is greater than first threshold.
Second aspect provides a kind of equipment for assessing microphone array consistency, comprising:
Acquiring unit, the N number of audio signal acquired respectively for obtaining N number of microphone, N number of microphone constitute Mike
Wind array, N >=2；
Processing unit, for determining in N number of microphone in addition to reference microphone according to N number of audio signal
Each microphone and the reference microphone between phase spectrum difference and/or power spectrum difference, the reference microphone is
Any one microphone in N number of microphone；
The processing unit is also used to according to each Mike in N number of microphone in addition to the reference microphone
Phase spectrum difference and/or power spectrum difference between wind and the reference microphone carry out consistency to N number of microphone and comment
Estimate.
In some possible implementations, the processing unit is specifically used for:
According in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between phase spectrum difference, assess the phase equalization between corresponding microphone and the reference microphone.
In some possible implementations, the processing unit is also used to:
Each microphone in N number of microphone in addition to the reference microphone is measured respectively with described with reference to Mike
Range difference of the wind to sound source；
According to measured range difference, calculate separately in N number of microphone each of in addition to the reference microphone
Fixed skew between microphone and the reference microphone；
According in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between fixed skew, calibrate its corresponding phase spectrum difference respectively.
In some possible implementations, the processing unit is specifically used for:
According to formulaCalculate separately in N number of microphone except the reference microphone it
Fixed skew between outer each microphone and the reference microphone,
Wherein, Yi(ω) indicates the frequency spectrum of i-th of microphone, Y1(ω) indicates that the frequency spectrum of reference microphone, ω indicate frequency
Rate, diIndicate the range difference of i-th of microphone and reference microphone to sound source, the c expression velocity of sound, 2 π ω di/ c indicates i-th of Mike
Fixed skew between wind and reference microphone.
In some possible implementations, the processing unit is specifically used for:
According in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between power spectrum difference, assess the amplitude coincidence between corresponding microphone and the reference microphone.
In some possible implementations, N number of audio signal is adopted in the environment of playing swept-frequency signal data
The signal of collection.
In some possible implementations, N number of audio signal is to play white Gaussian noise data or frequency sweep
The signal acquired in the environment of signal data.
In some possible implementations, the swept-frequency signal is Linear chirp, logarithm swept-frequency signal, linear step
Into any one in swept-frequency signal, logarithm stepping swept-frequency signal.
In some possible implementations, the processing unit is specifically used for:
Each audio signal in N number of audio signal is subjected to framing, obtains K signal frame of equal length, K >=
2；
Windowing process is done to each signal frame in the K signal frame, obtains K windowing signal frame；
FFT transform is done to each windowing signal frame in the K windowing signal frame, obtains K echo signal frame；
According to the corresponding K echo signal frame of each audio signal, determine in N number of microphone except described
The phase spectrum difference and/or power spectrum difference between each microphone and the reference microphone except reference microphone.
In some possible implementations, any two adjacent signals frame is overlapped R%, R > 0 in the K signal frame.
In some possible implementations, the R is 25 or 50.
In some possible implementations, i-th of audio signal is subjected to framing, obtains K signal of equal length
Frame is write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone collects the totalframes of signal, []TIt indicates
The transposition of vector or matrix.
In some possible implementations, the processing unit is specifically used for:
According to formulaIt determines in N number of microphone except the reference microphone
Except each microphone and the reference microphone between phase spectrum difference,
Wherein, imag () expression takes imaginary part, and ln () expression takes natural logrithm,Indicate i-th of microphone and ginseng
The phase spectrum difference between microphone is examined,Indicate j-th of echo signal frame of reference microphone,Indicate i-th
J-th of echo signal frame of a microphone,Indicate basic frequency.
In some possible implementations, the processing unit is specifically used for:
According to the corresponding K echo signal frame of each audio signal, the function of each audio signal is determined
Rate spectrum；
According to the power spectrum of each audio signal, determine in N number of microphone in addition to the reference microphone
Each microphone and the reference microphone between power spectrum difference.
In some possible implementations, the processing unit is specifically used for:
According to formulaThe power spectrum of each audio signal is calculated,
Wherein, Pi(ω) indicates the power spectrum of i-th of audio signal, Yi,j(ω) indicates the jth in i-th of audio signal
A echo signal frame, K indicate that each microphone collects the totalframes of signal, and ω indicates frequency.
In some possible implementations, the processing unit is specifically used for:
According to formula PDi(ω)=P1(ω)-Pi(ω) calculates every in addition to reference microphone in N number of microphone
Power spectrum difference between a microphone and the reference microphone,
Wherein, PDi(ω) indicates the power spectrum difference between i-th of microphone and reference microphone, P1(ω) indicates reference
The power spectrum of microphone, Pi(ω) indicates the power spectrum of i-th of microphone.
In some possible implementations, the processing unit is specifically used for:
Determine sample frequency F of the N number of microphone when carrying out audio signal samplesWith FFT points Nfft, using raising
Sound device plays white Gaussian noise data or swept-frequency signal data, controls N number of microphone and acquires N number of audio signal,
Wherein, if the data that are played of the loudspeaker are swept-frequency signal data, the swept-frequency signal data it is equal by M+1 segment length and
Equal signal is not constituted frequency,
In some possible implementations, the processing unit is also used to:
According to formulaThe frequency of every segment signal in the M+1 segment signal is calculated, and
According to formula Si(t)=sin (2 π fiT) every segment signal in the M+1 segment signal is calculated,
Wherein, fiIndicate the frequency of the i-th segment signal, FsIndicate sample frequency, NfftIndicate FFT points, Si(t) i-th is indicated
Segment signal, and S1(t) length is the integral multiple of cycle T, T=1/f1。
In some possible implementations, the swept-frequency signal data that the loudspeaker is played are write as following vector shape
Formula:
S (t)=[S0(t),S1(t),…,SM(t)]T
Wherein, S (t) indicates the swept-frequency signal data that loudspeaker is played, Si(t) the i-th segment signal is indicated,
[ ]TIndicate the transposition of vector or matrix.
In some possible implementations, N number of microphone collects N number of audio signal respectively, wherein i-th of wheat
Gram collected audio signal of wind is expressed as xiAnd x (t),i(t) it can be write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) the collected audio signal of i-th of microphone is indicated, K indicates that each microphone collects signal
Totalframes, []TIndicate the transposition of vector or matrix.
In some possible implementations, the acquiring unit is specifically used for:
N number of microphone is placed in test room, loudspeaker, N number of wheat are configured in the test room
Gram wind is located at the front of the loudspeaker；
It controls the loudspeaker and plays white Gaussian noise data or swept-frequency signal data, and control N number of Mike
Wind acquires N number of audio signal respectively.
In some possible implementations, there is noise reduction room environmental in the test room, the loudspeaker is audio
Special artificial mouth is tested, and the artificial mouth is calibrated with standard microphone before the use.
In some possible implementations, the loudspeaker is controlled in the processing unit and plays white Gaussian noise data
Or before swept-frequency signal data, the acquiring unit is also used to:
Under quiet environment, N number of microphone is obtained in the first duration T1First audio data X of interior acquisition1(n)；
In the environment of playing white Gaussian noise data or swept-frequency signal data, N number of microphone is obtained second
Duration T2The second audio data X of interior acquisition2(n)；
The processing unit is triggered according to formulaSignal to Noise Ratio (SNR) is calculated, and is ensured described
SNR is greater than first threshold.
The third aspect provides a kind of device for assessing microphone array consistency, comprising:
Memory, for storing program and data；And
Processor, for calling and running the program and data that store in the memory；
The device is configured as executing the method in above-mentioned first aspect or its any possible implementation.
Fourth aspect provides the system of assessment microphone array consistency, comprising:
Constitute N number of microphone of microphone array, N >=2；
At least one audio-source；
Device stores in the memory including the memory for storing program and data and for calling and running
The processor of program and data, the device are configured as the method in above-mentioned first aspect or its any possible implementation.
5th aspect, provides a kind of computer storage medium, is stored with program code in the computer storage medium, should
Program code can serve to indicate that the method executed in above-mentioned first aspect or its any possible implementation.
6th aspect, provides a kind of computer program product comprising instruction, when running on computers, makes to succeed in one's scheme
Calculation machine executes the method in above-mentioned first aspect or its any possible implementation.
Detailed description of the invention
Fig. 1 is the schematic flow chart of the method for the assessment microphone array consistency of the embodiment of the present application.
Fig. 2 is the test environment schematic according to the embodiment of the present application.
Fig. 3 is the schematic diagram according to the calculating phase spectrum difference of the embodiment of the present application.
Fig. 4 is the schematic diagram according to the calculating power spectrum difference of the embodiment of the present application.
Fig. 5 is the schematic diagram of the phase spectrum difference between two microphones according to the embodiment of the present application.
Fig. 6 is the schematic diagram of the phase spectrum difference after calibrating between two microphones according to the embodiment of the present application.
Fig. 7 a is the schematic diagram according to the power spectrum of two microphones of the embodiment of the present application.
Fig. 7 b is the schematic diagram of the power spectrum difference between two microphones according to the embodiment of the present application.
Fig. 8 is the schematic diagram according to a kind of equipment of assessment microphone array consistency of the embodiment of the present application.
Fig. 9 is the schematic diagram according to a kind of device of assessment microphone array consistency of the embodiment of the present application.
Figure 10 is the schematic diagram according to a kind of system of assessment microphone array consistency of the embodiment of the present application.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application is clearly retouched
It states.
Microphone array (Microphone Array) refers to be made of the microphone (acoustic sensor) of certain amount, is used
Come the system that the spatial character of sound field is sampled and handled.The difference between the phase of sound wave is received using two microphones
It is different that sound wave is filtered, environmental background sound can be disposed to greatest extent, only the remaining sound wave needed.
Multicenter voice enhancing technique algorithm assumed condition be multiple microphones in microphone array target voice at
Divide high correlation, target voice is uncorrelated to non-targeted interference, therefore the consistency in microphone array between different microphones
Directly affect algorithm performance.
The qualitative assessment of microphone consistency can be used for instructing the design of microphone and the design of microphone array, Mike
Circuit, electronic component, the acoustic construction of wind array can all influence the consistency of microphone, can be by when designing microphone array
Influence of the item test various factors to consistency, so that the design of microphone consistency be made to reach system requirements.
The qualitative assessment of microphone consistency can be used for comparing the robustness of algorithms of different, reach same voice enhancing
The premise of performance, lower to coincident indicator requirement, algorithm robustness is better.
In the embodiment of the present application, consistency is measured in terms of amplitude spectrum difference and phase spectrum difference two, it is objective to have
Property and accuracy, and quantitative method for assessing consistency can objectively instruct the design of microphone array, it also can be objective
Comparison multicenter voice enhancing algorithm robustness.
Hereinafter, the method for the assessment microphone array consistency of the embodiment of the present application is discussed in detail in conjunction with Fig. 1 to Fig. 7.
Fig. 1 is the schematic flow chart of the method for the assessment microphone array consistency of the application one embodiment.Ying Li
The step of solution, Fig. 1 shows this method or operation, but these steps or operation are only examples, and the embodiment of the present application can also be held
The deformation of other operations of row or each operation in Fig. 1.This method can be held by the device of assessment microphone array consistency
Row, wherein the device of the assessment microphone array consistency can be mobile phone, tablet computer, portable computer, individual digital and help
Manage (Personal Digital Assistant, PDA) etc..
S110 obtains N number of audio signal that N number of microphone acquires respectively, N number of microphone composition microphone array, and N >=
2。
When carrying out compliance evaluation to N number of microphone, need to limit environment locating for N number of microphone, i.e. N number of audio
Signal is acquired under special test environment.
Specifically, as shown in Fig. 2, the microphone array 201 being made of N number of microphone is placed in test room 202
It is interior, and loudspeaker 203 is configured in the test room 202, which is being particularly located at the loudspeaker 203 just
Front, the microphone array 201 connect the control equipment 204 of such as computer with the loudspeaker 203.The control equipment 204 can
Specific audio data is played to control the loudspeaker 203, for example, white Gaussian noise data or swept-frequency signal data are played,
Meanwhile the control equipment 204 can obtain N number of audio letter of N number of microphone distribution collection from the microphone array 201
Number.
It should be noted that microphone compliance evaluation requires the signal-to-noise ratio of the audio signal of acquisition sufficiently high, background is made an uproar
Sound is weak enough, therefore tests environmental requirement under quiet environment.Particularly, noise reduction room environmental is required in test room 202.
Loudspeaker 203 requires noise relatively high, and frequency response curve is flat, and particularly, loudspeaker uses audio-frequency test Special artificial
Mouth, and calibrated before use with standard microphone.Microphone array 201 is placed on the front of loudspeaker 203, particularly,
Ask the position for being placed on standard microphone calibration.
Optionally, before carrying out formal audio signal sample, it is also necessary to carry out signal-to-noise ratio to above-mentioned test environment
(signal-to-noise ratio, SNR) detection.
Specifically, under test environment as shown in Figure 2, firstly, (i.e. loudspeaker 203, which is in, closes under quiet environment
Closed state), N number of microphone is obtained in the first duration T1First audio data X of interior acquisition1(n)；Then, white Gaussian is being played
(i.e. the control equipment 204 controls the loudspeaker 203 and plays white Gaussian noise in the environment of noise data or swept-frequency signal data
Data or swept-frequency signal data), N number of microphone is obtained in the second duration T2The second audio data X of interior acquisition2(n)；It connects
, 1 calculate SNR according to the following formula；Finally, then detection passes through when SNR is greater than given threshold, otherwise detects and do not pass through.
Wherein, T1Indicate the first duration, T2Indicate the second duration, X1(n) the first audio data, X are indicated2(n) second is indicated
Audio data.
It should be noted that if detection does not pass through, need that above-mentioned test environment is adjusted or is calibrated, eliminate
It may be to the factor that signal-to-noise ratio impacts, until being greater than given threshold according to the SNR calculated of above-mentioned formula 1.
It optionally, in the embodiment of the present application, specifically can be with using above-mentioned test environment shown in Fig. 2 acquisition audio signal
Include:
Determine sample frequency F of the N number of microphone when carrying out audio signal samplesWith FFT points Nfft, use loudspeaking
Device plays white Gaussian noise data or swept-frequency signal data, N number of microphone acquire N number of audio signal.
Optionally, FFT points NfftFor even number, generally 32,64,128 ..., 1024 etc., it counts more, operand
It saves bigger.
It should be noted that if the data that the loudspeaker is played are swept-frequency signal data, the swept-frequency signal data are by M+1
Segment length is equal and the signal of frequency not etc. is constituted,
It is alternatively possible to 2 frequency for calculating every segment signal in the M+1 segment signal according to the following formula, and according to as follows
Formula 3 calculates every segment signal in the M+1 segment signal.
Wherein, fiIt is the frequency of the i-th segment signal, FsIt is sample frequency, NfftIndicate FFT points.
Si(t)=sin (2 π fiT) formula 3
Wherein, Si(t) the i-th segment signal, f are indicatediIt is the frequency of the i-th segment signal.
It should be noted that the first segment signal S1(t) length is the integral multiple of cycle T, T=1/f1。
Optionally, the swept-frequency signal data that loudspeaker is played can be write as following vector form:
S (t)=[S0(t),S1(t),…,SM(t)]T
Wherein, S (t) indicates the swept-frequency signal data that loudspeaker is played, Si(t) the i-th segment signal is indicated,
[ ]TIndicate the transposition of vector or matrix.
Optionally, N number of microphone collects N number of audio signal respectively, wherein the collected audio signal of i-th of microphone
It is expressed as xiAnd x (t),i(t) it can be write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) the collected audio signal of i-th of microphone is indicated, K indicates that each microphone collects signal
Totalframes, []TIndicate the transposition of vector or matrix.
S120 determines each microphone in N number of microphone in addition to reference microphone according to N number of audio signal
Phase spectrum difference and/or power spectrum difference between the reference microphone, the reference microphone are appointing in N number of microphone
It anticipates a microphone.
Optionally, in the embodiment of the present application, after N number of audio signal sample arrives, audio signal point can be passed through
Frame does FFT transform to every frame windowing signal, seeks the phase spectrum difference between different microphones to every frame audio signal adding window.
Specifically, as shown in Figure 3, it is assumed that N number of audio signal is x1(t),x2(t),…,xN(t), which is believed
Each audio signal in number carries out framing, obtains K signal frame of equal length, K >=2, for example, by i-th of audio signal
Framing is carried out, K signal frame for obtaining equal length is write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone collects the totalframes of signal, []TIt indicates
The transposition of vector or matrix；
Windowing process is done to each signal frame in the K signal frame, K windowing signal frame is obtained, for example, to i-th
J-th of frame x of audio signali,jAdding window obtains j-th of windowing signal frame y of i-th of audio signali,j=xi,j×Win；
FFT transform is done to each windowing signal frame in the K windowing signal frame, obtains K echo signal frame, for example,
To j-th of windowing signal frame y of i-th of audio signali,j(t) FFT transform is done, j-th of target of i-th of audio signal is obtained
Signal frame Yi,j(ω)；
According to the corresponding K echo signal frame of each audio signal, determine in N number of microphone except this is with reference to Mike
The phase spectrum difference between each microphone and the reference microphone except wind, for example, it is assumed that the master of j-th of echo signal frame
Frequency isThen can be in basic frequency with according to the following formula 4 i-th of microphone of calculating and reference microphoneThe phase spectrum at place
Difference.
Wherein, imag () expression takes imaginary part, and ln () expression takes natural logrithm,Indicate i-th of microphone with
Phase spectrum difference between reference microphone,Indicate j-th of echo signal frame of reference microphone,Indicate the
J-th of echo signal frame of i microphone,Indicate basic frequency.
It should be noted that in above-mentioned Fig. 3 being calculated separately and removing using first microphone as reference microphone
The phase spectrum difference between each microphone and first microphone except first microphone, and the first microphone diaphone
Frequency signal x1(t), second microphone corresponds to audio signal x2(t) ..., N microphone corresponds to audio signal xN(t)。
Optionally, K indicates that each microphone receives the totalframes of signal.
It should be noted that bring truncation effect when windowing process is used to eliminate framing.It is alternatively possible to be to the K
Each signal frame in a signal frame is done plus Hamming window processing.
In some possible implementations, any two adjacent signals frame is overlapped R%, R > 0 in the K signal frame.Example
Such as, which is 25 or 50.In other words, any two adjacent signals frame overlapping 25% or 50% in the K signal frame.
Optionally, signal amplitude remains unchanged after being overlapped adding window.
It should be understood that each frame signal after overlapping has the ingredient of previous frame, prevent discontinuous between two frames.
Optionally, in the embodiment of the present application, when carrying out phase equalization assessment, which is to play
The signal acquired in the environment of swept-frequency signal data.In other words, when computationally stating phase spectrum difference, N number of audio signal
It is the signal acquired in the environment of playing swept-frequency signal data.
It is consequently possible to calculate the phase difference of any frequencies omega is out to get between i-th of microphone and reference microphone
Phase spectrum difference PDiffi(ω), i.e., it is above-mentioned
Optionally, in the embodiment of the present application, after N number of audio signal sample arrives, audio signal point can be passed through
Frame does FFT transform to every frame windowing signal, seeks the power of every frame signal after FFT transform to every frame audio signal adding window
Spectrum, seeks the power spectrum difference between different microphones.
Specifically, it is assumed that N number of audio signal is x1(t),x2(t),…,xN(t), which is believed
Each audio signal in number carries out framing, obtains K signal frame of equal length, K >=2, for example, by i-th of audio signal
Framing is carried out, K signal frame for obtaining equal length is write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone receives the totalframes of signal, []TIt indicates
The transposition of vector or matrix；
Windowing process is done to each signal frame in the K signal frame, K windowing signal frame is obtained, for example, to i-th
J-th of frame x of audio signali,jAdding window obtains j-th of windowing signal frame y of i-th of audio signali,j=xi,j×Win；
FFT transform is done to each windowing signal frame in the K windowing signal frame, obtains K echo signal frame, for example,
To j-th of windowing signal frame y of i-th of audio signali,j(t) FFT transform is done, j-th of target of i-th of audio signal is obtained
Signal frame Yi,j(ω)；
According to the corresponding K echo signal frame of each audio signal, the power spectrum of each audio signal, example are determined
Such as, according to the following formula 5 calculate i-th of audio signal power spectrum；
According to the power spectrum of each audio signal, determine in N number of microphone each of in addition to the reference microphone
Power spectrum difference between microphone and the reference microphone, for example, 6 calculating i-th of microphone and the ginseng according to the following formula
Examine the power spectrum difference between microphone.
Wherein, Pi(ω) indicates the power spectrum of i-th of audio signal, Yi,j(ω) indicates the jth in i-th of audio signal
A echo signal frame, ω indicate frequency, and K indicates that each microphone collects the totalframes of signal.
PDi(ω)=P1(ω)-Pi(ω) formula 6
Wherein, PDi(ω) indicates the power spectrum difference between i-th of microphone and reference microphone, P1(ω) indicates reference
The power spectrum of microphone, Pi(ω) indicates the power spectrum of i-th of microphone.
It should be noted that in above-mentioned Fig. 4 being calculated separately and removing using first microphone as reference microphone
The power spectrum difference between each microphone and first microphone except first microphone, and the first microphone diaphone
Frequency signal x1(t), second microphone corresponds to audio signal x2(t) ..., N microphone corresponds to audio signal xN(t)。
It should be noted that bring truncation effect when windowing process is used to eliminate framing.It is alternatively possible to be to the K
Each signal frame in a signal frame is done plus Hamming window processing.
In some possible implementations, any two adjacent signals frame is overlapped R%, R > 0 in the K signal frame.Example
Such as, which is 25 or 50.In other words, any two adjacent signals frame overlapping 25% or 50% in the K signal frame.
Optionally, signal amplitude remains unchanged after being overlapped adding window.
It should be understood that each frame signal after overlapping has the ingredient of previous frame, prevent discontinuous between two frames.
Optionally, in the embodiment of the present application, when carrying out amplitude coincidence assessment, which is to play
The signal acquired in the environment of white Gaussian noise data or swept-frequency signal data.In other words, power spectral difference is computationally stated
When value, which is the signal acquired in the environment of playing white Gaussian noise data or swept-frequency signal data.
S130, according in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between phase spectrum difference and/or power spectrum difference, compliance evaluation is carried out to the N number of microphone.
Specifically, phase spectrum difference is for carrying out phase equalization assessment and power spectrum difference for carrying out amplitude one
The assessment of cause property.
Optionally, in the embodiment of the present application, according in N number of microphone each of in addition to the reference microphone
Phase spectrum difference between microphone and the reference microphone assesses the phase between corresponding microphone and the reference microphone
Bit integrity.
It should be noted that the phase spectrum difference between two microphones is smaller, the phase between the two microphones is indicated
Bit integrity is better.
For example, the phase spectrum difference between microphone 1 and reference microphone is A, A is smaller, indicates microphone 1 and refers to wheat
Phase equalization between gram wind is better.
It is alternatively possible to a threshold value be arranged, if the phase spectrum difference between two microphones is less than this threshold value, table
Show that the phase equalization between the two microphones meets design requirement, the consistency between the two microphones is to multichannel language
Sound enhancing algorithm influence can ignore or the two microphones between consistency to multicenter voice enhancing algorithm do not have
It influences.
It should be noted that above-mentioned threshold value can enhance algorithm flexible configuration according to different multicenter voices.
It should be noted that because when acquiring data, the distance of different microphones to sound source be difficult to it is completely the same, so not
With between microphone, there are a fixed skews.
Optionally, in the embodiment of the present application, above-mentioned phase spectrum difference can be calibrated by fixed skew.
Specifically, each microphone in N number of microphone in addition to the reference microphone is measured respectively and this refers to wheat
Gram wind to sound source range difference, for example, diIndicate the range difference of i-th of microphone with reference microphone to sound source；
According to measured range difference, each Mike in N number of microphone in addition to the reference microphone is calculated separately
Fixed skew between wind and the reference microphone, for example, i-th of microphone and reference can be calculated with according to the following formula 7
Fixed skew between microphone；
According to each microphone in N number of microphone in addition to the reference microphone and consolidating between the reference microphone
Phase bit is poor, calibrates its corresponding phase spectrum difference respectively.
Wherein, Yi(ω) indicates the frequency spectrum of i-th of microphone, Y1(ω) indicates that the frequency spectrum of reference microphone, ω indicate frequency
Rate, diIndicate the range difference of i-th of microphone and reference microphone to sound source, the c expression velocity of sound, 2 π ω di/ c indicates i-th of Mike
Fixed skew between wind and reference microphone.
It should be noted that fixed skew and signal frequency meet linear relationship, therefore, it is possible to use linear fit
Mode determines fixed skew.
For example, the fixed skew between microphone 1 and reference microphone is A, between microphone 1 and reference microphone
Phase spectrum difference is B, as shown in figure 5, straight line portion indicates the stationary phase between the obtained microphone 1 of fitting and reference microphone
Potential difference, curved portion indicate the phase spectrum difference between microphone 1 and reference microphone, and overall performance goes out, with frequency from
0Hz increases to 8000Hz, and the phase spectrum difference between microphone 1 and reference microphone is decreased to -2 radians from 0 radian.Calibrate it
Afterwards, the phase spectrum difference between microphone 1 and reference microphone is C, as shown in curve in Fig. 6, at this point, C=B-A, entirety
Show, as frequency increases to 8000Hz from 0Hz, the phase spectrum difference between microphone 1 and reference microphone 0 radian with
It is fluctuated between ± 0.5 radian.
By Fig. 5 and Fig. 6 comparison it is found that fixed skew the phase spectrum difference between two microphones can be caused it is biggish
It influences, therefore, when carrying out amplitude coincidence assessment to two microphones, needs to eliminate the fixed skew institute between two microphones
Caused by influence.
Optionally, in the embodiment of the present application, according to each Mike in N number of microphone in addition to the reference microphone
It is consistent with the amplitude between the reference microphone to assess corresponding microphone for power spectrum difference between wind and the reference microphone
Property.
It should be noted that the power spectrum difference between two microphones is smaller, the width between the two microphones is indicated
It is better to spend consistency.
For example, as shown in fig. 7, specifically, Fig. 7 a shows the power spectrum of microphone 1 and the power spectrum of reference microphone,
Fig. 7 b shows the power spectrum difference between microphone 1 and reference microphone, the power spectrum between microphone 1 and reference microphone
It is not much different, and maximum value < ± 1 decibel (dB) of its power spectrum difference.
It is alternatively possible to a threshold value be arranged, if the power spectrum difference between two microphones is less than this threshold value, table
Show that the amplitude coincidence between the two microphones meets design requirement, the consistency between the two microphones is to multichannel language
Sound enhancing algorithm influence can ignore or the two microphones between consistency to multicenter voice enhancing algorithm do not have
It influences.
It should be noted that above-mentioned threshold value can enhance algorithm flexible configuration according to different multicenter voices.
Optionally, in the embodiment of the present application, can test item by item the circuit of such as microphone array, electronic component,
Influence of the factors such as acoustic construction to microphone consistency specifically, can be guidance to instruct the calibration of microphone array
The design of microphone and the design of microphone array, the robustness of assessment multichannel enhancing algorithm.
Therefore, in the embodiment of the present application, the N number of audio signal that can be acquired respectively according to N number of microphone, determines each
Phase spectrum difference and/or power spectrum difference between microphone and reference microphone are commented to carry out consistency to N number of microphone
Estimate, eliminates influence of the consistency to multicenter voice enhancing algorithm between microphone, promote user experience.
Optionally, as shown in figure 8, the embodiment of the present application provides a kind of equipment 800 for assessing microphone array consistency,
Include:
Acquiring unit 810, the N number of audio signal acquired respectively for obtaining N number of microphone, N number of microphone are constituted
Microphone array, N >=2；
Processing unit 820, for according to N number of audio signal, determine in N number of microphone except reference microphone it
Phase spectrum difference and/or power spectrum difference between outer each microphone and the reference microphone, the reference microphone
For any one microphone in N number of microphone；
The processing unit 820 is also used to according to each wheat in N number of microphone in addition to the reference microphone
Phase spectrum difference and/or power spectrum difference gram between wind and the reference microphone carry out consistency to N number of microphone
Assessment.
Optionally, the processing unit 820 is specifically used for:
According in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between phase spectrum difference, assess the phase equalization between corresponding microphone and the reference microphone.
Optionally, the processing unit 820 is also used to:
Each microphone in N number of microphone in addition to the reference microphone is measured respectively with described with reference to Mike
Range difference of the wind to sound source；
According to measured range difference, calculate separately in N number of microphone each of in addition to the reference microphone
Fixed skew between microphone and the reference microphone；
According in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between fixed skew, calibrate its corresponding phase spectrum difference respectively.
Optionally, the processing unit 820 is specifically used for:
According to formulaCalculate separately in N number of microphone except the reference microphone it
Fixed skew between outer each microphone and the reference microphone,
Wherein, Yi(ω) indicates the frequency spectrum of i-th of microphone, Y1(ω) indicates that the frequency spectrum of reference microphone, ω indicate frequency
Rate, diIndicate the range difference of i-th of microphone and reference microphone to sound source, the c expression velocity of sound, 2 π ω di/ c indicates i-th of Mike
Fixed skew between wind and reference microphone.
Optionally, the processing unit 820 is specifically used for:
According in N number of microphone in addition to the reference microphone each microphone and the reference microphone it
Between power spectrum difference, assess the amplitude coincidence between corresponding microphone and the reference microphone.
Optionally, N number of audio signal is the signal acquired in the environment of playing swept-frequency signal data.
Optionally, N number of audio signal is in the environment of playing white Gaussian noise data or swept-frequency signal data
The signal of acquisition.
Optionally, the swept-frequency signal is Linear chirp, logarithm swept-frequency signal, linear stepping swept-frequency signal, logarithm
Any one in stepping swept-frequency signal.
Optionally, the processing unit 820 is specifically used for:
Each audio signal in N number of audio signal is subjected to framing, obtains K signal frame of equal length, K >=
2；
Windowing process is done to each signal frame in the K signal frame, obtains K windowing signal frame；
FFT transform is done to each windowing signal frame in the K windowing signal frame, obtains K echo signal frame；
According to the corresponding K echo signal frame of each audio signal, determine in N number of microphone except described
The phase spectrum difference and/or power spectrum difference between each microphone and the reference microphone except reference microphone.
Optionally, any two adjacent signals frame is overlapped R%, R > 0 in the K signal frame.
Optionally, the R is 25 or 50.
Optionally, i-th of audio signal is subjected to framing, K signal frame for obtaining equal length is write as following vector shape
Formula:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone collects the totalframes of signal, []TIt indicates
The transposition of vector or matrix.
Optionally, the processing unit 820 is specifically used for:
According to formulaIt determines in N number of microphone except the reference microphone
Except each microphone and the reference microphone between phase spectrum difference,
Wherein, imag () expression takes imaginary part, and ln () expression takes natural logrithm,Indicate i-th of microphone and ginseng
The phase spectrum difference between microphone is examined,Indicate j-th of echo signal frame of reference microphone,Indicate i-th
J-th of echo signal frame of a microphone,Indicate basic frequency.
Optionally, the processing unit 820 is specifically used for:
According to the corresponding K echo signal frame of each audio signal, the function of each audio signal is determined
Rate spectrum；
According to the power spectrum of each audio signal, determine in N number of microphone in addition to the reference microphone
Each microphone and the reference microphone between power spectrum difference.
Optionally, the processing unit 820 is specifically used for:
According to formulaThe power spectrum of each audio signal is calculated,
Wherein, Pi(ω) indicates the power spectrum of i-th of audio signal, Yi,j(ω) indicates the jth in i-th of audio signal
A echo signal frame, K indicate that each microphone collects the totalframes of signal, and ω indicates frequency.
Optionally, the processing unit 820 is specifically used for:
According to formula PDi(ω)=P1(ω)-Pi(ω) calculates every in addition to reference microphone in N number of microphone
Power spectrum difference between a microphone and the reference microphone,
Wherein, PDi(ω) indicates the power spectrum difference between i-th of microphone and reference microphone, P1(ω) indicates reference
The power spectrum of microphone, Pi(ω) indicates the power spectrum of i-th of microphone.
Optionally, the processing unit 820 is specifically used for:
Determine sample frequency F of the N number of microphone when carrying out audio signal samplesWith FFT points Nfft, using raising
Sound device plays white Gaussian noise data or swept-frequency signal data, controls N number of microphone and acquires N number of audio signal,
Wherein, if the data that are played of the loudspeaker are swept-frequency signal data, the swept-frequency signal data it is equal by M+1 segment length and
Equal signal is not constituted frequency,
Optionally, the processing unit 820 is also used to:
According to formulaThe frequency of every segment signal in the M+1 segment signal is calculated, and
According to formula Si(t)=sin (2 π fiT) every segment signal in the M+1 segment signal is calculated,
Wherein, fiIndicate the frequency of the i-th segment signal, FsIndicate sample frequency, NfftIndicate FFT points, Si(t) i-th is indicated
Segment signal, and S1(t) length is the integral multiple of cycle T, T=1/f1。
Optionally, the swept-frequency signal data that the loudspeaker is played are write as following vector form:
S (t)=[S0(t),S1(t),…,SM(t)]T
Wherein, S (t) indicates the swept-frequency signal data that loudspeaker is played, Si(t) the i-th segment signal is indicated,
[ ]TIndicate the transposition of vector or matrix.
Optionally, N number of microphone collects N number of audio signal respectively, wherein the collected audio of i-th of microphone
Signal is expressed as xiAnd x (t),i(t) it can be write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) the collected audio signal of i-th of microphone is indicated, K indicates that each microphone collects signal
Totalframes, []TIndicate the transposition of vector or matrix.
Optionally, the acquiring unit 810 is specifically used for:
N number of microphone is placed in test room, loudspeaker, N number of wheat are configured in the test room
Gram wind is located at the front of the loudspeaker；
It controls the loudspeaker and plays white Gaussian noise data or swept-frequency signal data, and control N number of Mike
Wind acquires N number of audio signal respectively.
Optionally, there is noise reduction room environmental in the test room, the loudspeaker is audio-frequency test Special artificial mouth, and
The artificial mouth is calibrated with standard microphone before the use.
Optionally, the loudspeaker is controlled in the processing unit 820 play white Gaussian noise data or swept-frequency signal
Before data, the acquiring unit 810 is also used to:
Under quiet environment, N number of microphone is obtained in the first duration T1First audio data X of interior acquisition1(n)；
In the environment of playing white Gaussian noise data or swept-frequency signal data, N number of microphone is obtained second
Duration T2The second audio data X of interior acquisition2(n)；
The processing unit 820 is triggered according to formulaSignal to Noise Ratio (SNR) is calculated, and ensures institute
SNR is stated greater than first threshold.
Optionally, as shown in figure 9, the embodiment of the present application provides a kind of device 900 for assessing microphone array consistency,
Include:
Memory 910, for storing program and data；And
Processor 920, for calling and running the program and data that store in the memory；
The device 900 is configured as executing method shown in above-mentioned Fig. 1 to 7.
Optionally, as shown in Figure 10, the embodiment of the present application provides a kind of system for assessing microphone array consistency
1000, comprising:
Constitute N number of microphone of microphone array 1010, N >=2；
At least one audio-source 1020；
Device 1030, including the memory 1031 for storing program and data and for calling and running the memory
The program of middle storage and the processor 1032 of data, the device 1030 are configured as method shown in above-mentioned Fig. 1 to 7.
It should be understood that magnitude of the sequence numbers of the above procedures are not meant to execute suitable in the various embodiments of the application
Sequence it is successive, the execution of each process sequence should be determined by its function and internal logic, the implementation without coping with the embodiment of the present application
Process constitutes any restriction.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
Scope of the present application.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided herein, it should be understood that disclosed systems, devices and methods, it can be with
It realizes by another way.For example, the apparatus embodiments described above are merely exemplary, for example, the unit is drawn
Point, only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units or components can
To combine or be desirably integrated into another system, or some features can be ignored or not executed.Another point, it is shown or beg for
The mutual coupling, direct-coupling or communication connection of opinion can be through some interfaces, the INDIRECT COUPLING of device or unit
Or communication connection, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, each functional unit in each embodiment of the application can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, the technical solution of the application is substantially
The part of the part that contributes to existing technology or the technical solution can embody in the form of software products in other words
Come, which is stored in a storage medium, including some instructions are used so that a computer equipment (can
To be personal computer, server or the network equipment etc.) execute each embodiment the method for the application all or part
Step.And storage medium above-mentioned include: USB flash disk, it is mobile hard disk, read-only memory (ROM, Read-Only Memory), random
Access various Jie that can store program code such as memory (RAM, Random Access Memory), magnetic or disk
Matter.
The above, the only specific embodiment of the application, but the protection scope of the application is not limited thereto, it is any
Those familiar with the art within the technical scope of the present application, can easily think of the change or the replacement, and should all contain
Lid is within the scope of protection of this application.Therefore, the protection scope of the application should be subject to the scope of protection of the claims.
Claims (48)
1. a kind of method for assessing microphone array consistency characterized by comprising
N number of audio signal that N number of microphone acquires respectively is obtained, N number of microphone constitutes microphone array, N >=2；
According to N number of audio signal, determine each microphone in N number of microphone in addition to reference microphone with it is described
Phase spectrum difference and/or power spectrum difference between reference microphone, the reference microphone are appointing in N number of microphone
It anticipates a microphone；
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Phase spectrum difference and/or power spectrum difference carry out compliance evaluation to N number of microphone.
2. the method according to claim 1, wherein it is described according in N number of microphone remove reference microphone
Except each microphone and the reference microphone between phase spectrum difference, consistency is carried out to the N number of microphone and is commented
Estimate, comprising:
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Phase spectrum difference assesses the phase equalization between corresponding microphone and the reference microphone.
3. according to the method described in claim 2, it is characterized in that, the method also includes:
Each microphone in N number of microphone in addition to the reference microphone is measured respectively to arrive with the reference microphone
The range difference of sound source；
According to measured range difference, each Mike in N number of microphone in addition to the reference microphone is calculated separately
Fixed skew between wind and the reference microphone；
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Fixed skew calibrates its corresponding phase spectrum difference respectively.
4. according to the method described in claim 3, it is characterized in that, the distance according to measured by, calculates separately described N number of
The fixed skew between each microphone and the reference microphone in microphone in addition to the reference microphone, packet
It includes:
According to formulaIt calculates separately in N number of microphone in addition to the reference microphone
Fixed skew between each microphone and the reference microphone,
Wherein, Yi(ω) indicates the frequency spectrum of i-th of microphone, Y1(ω) indicates that the frequency spectrum of reference microphone, ω indicate frequency, di
Indicate the range difference of i-th of microphone and reference microphone to sound source, the c expression velocity of sound, 2 π ω di/ c indicate i-th microphone with
Fixed skew between reference microphone.
5. method according to claim 1 to 4, which is characterized in that described to be removed according in N number of microphone
The phase spectrum difference between each microphone and the reference microphone except reference microphone, to N number of microphone into
Row compliance evaluation, comprising:
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Power spectrum difference assesses the amplitude coincidence between corresponding microphone and the reference microphone.
6. method according to any one of claim 2 to 4, which is characterized in that N number of audio signal is swept in broadcasting
The signal acquired in the environment of frequency signal data.
7. according to the method described in claim 5, it is characterized in that, N number of audio signal is to play white Gaussian noise number
According to or swept-frequency signal data in the environment of the signal that acquires.
8. method according to claim 6 or 7, which is characterized in that the swept-frequency signal is Linear chirp, logarithm is swept
Frequency signal, linear stepping swept-frequency signal, any one in logarithm stepping swept-frequency signal.
9. method according to any one of claim 1 to 8, which is characterized in that it is described according to N number of audio signal,
Determine each microphone in N number of microphone in addition to reference microphone and the Phase spectrum difference between the reference microphone
Value and/or power spectrum difference, comprising:
Each audio signal in N number of audio signal is subjected to framing, obtains K signal frame of equal length, K >=2；
Windowing process is done to each signal frame in the K signal frame, obtains K windowing signal frame；
FFT transform is done to each windowing signal frame in the K windowing signal frame, obtains K echo signal frame；
According to the corresponding K echo signal frame of each audio signal, determine in N number of microphone except the reference
The phase spectrum difference and/or power spectrum difference between each microphone and the reference microphone except microphone.
10. according to the method described in claim 9, it is characterized in that, any two adjacent signals frame weight in the K signal frame
Folded R%, R > 0.
11. according to the method described in claim 10, it is characterized in that, the R is 25 or 50.
12. the method according to any one of claim 9 to 11, which is characterized in that divided i-th of audio signal
Frame, K signal frame for obtaining equal length are write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone collects the totalframes of signal, []TIndicate vector
Or the transposition of matrix.
13. the method according to any one of claim 9 to 12, which is characterized in that described to be believed according to each audio
Number corresponding K echo signal frame, determines each microphone in N number of microphone in addition to the reference microphone
Phase spectrum difference between the reference microphone, comprising:
According to formulaIt determines in N number of microphone in addition to the reference microphone
Each microphone and the reference microphone between phase spectrum difference,
Wherein, imag () expression takes imaginary part, and ln () expression takes natural logrithm,It indicates i-th of microphone and refers to wheat
Phase spectrum difference between gram wind,Indicate j-th of echo signal frame of reference microphone,Indicate i-th of wheat
J-th of echo signal frame of gram wind,Indicate basic frequency.
14. the method according to any one of claim 9 to 13, which is characterized in that described to be believed according to each audio
Number corresponding K echo signal frame, determines each microphone in N number of microphone in addition to the reference microphone
Power spectrum difference between the reference microphone, comprising:
According to the corresponding K echo signal frame of each audio signal, the power spectrum of each audio signal is determined；
According to the power spectrum of each audio signal, determine every in addition to the reference microphone in N number of microphone
Power spectrum difference between a microphone and the reference microphone.
15. according to the method for claim 14, which is characterized in that described corresponding described according to each audio signal
K echo signal frame determines the power spectrum of each audio signal, comprising:
According to formulaThe power spectrum of each audio signal is calculated,
Wherein, Pi(ω) indicates the power spectrum of i-th of audio signal, Yi,j(ω) indicates j-th of target in i-th of audio signal
Signal frame, K indicate that each microphone collects the totalframes of signal, and ω indicates frequency.
16. method according to claim 14 or 15, which is characterized in that the power according to each audio signal
Spectrum, determines each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Power spectrum difference, comprising:
According to formula PDi(ω)=P1(ω)-Pi(ω) calculates each wheat in N number of microphone in addition to reference microphone
Power spectrum difference gram between wind and the reference microphone,
Wherein, PDi(ω) indicates the power spectrum difference between i-th of microphone and reference microphone, P1(ω) indicates to refer to Mike
The power spectrum of wind, Pi(ω) indicates the power spectrum of i-th of microphone.
17. according to claim 1 to method described in any one of 16, which is characterized in that the N number of microphone of acquisition is adopted respectively
N number of audio signal of collection, comprising:
Determine sample frequency F of the N number of microphone when carrying out audio signal samplesWith FFT points Nfft, broadcast using loudspeaker
White Gaussian noise data or swept-frequency signal data are put, N number of microphone acquires N number of audio signal, wherein if described
The data that loudspeaker is played are swept-frequency signal data, the swept-frequency signal data are equal by M+1 segment length and frequency not etc.
Signal is constituted,
18. according to the method for claim 17, which is characterized in that
According to formulaThe frequency of every segment signal in the M+1 segment signal is calculated, and
According to formula Si(t)=sin (2 π fiT) every segment signal in the M+1 segment signal is calculated,
Wherein, fiIndicate the frequency of the i-th segment signal, FsIndicate sample frequency, NfftIndicate FFT points, Si(t) i-th section of letter is indicated
Number, and S1(t) length is the integral multiple of cycle T, T=1/f1。
19. according to the method for claim 18, which is characterized in that the swept-frequency signal data that the loudspeaker is played are write as
Following vector form:
S (t)=[S0(t),S1(t),…,SM(t)]T
Wherein, S (t) indicates the swept-frequency signal data that loudspeaker is played, Si(t) the i-th segment signal is indicated,[]TTable
Show the transposition of vector or matrix.
20. according to claim 1 to method described in any one of 19, which is characterized in that N number of microphone collects respectively
N number of audio signal, wherein the collected audio signal of i-th of microphone is expressed as xiAnd x (t),i(t) it can be write as following vector
Form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) the collected audio signal of i-th of microphone is indicated, K indicates that each microphone collects total frame of signal
Number, []TIndicate the transposition of vector or matrix.
21. according to claim 1 to method described in any one of 20, which is characterized in that the N number of microphone of acquisition is adopted respectively
N number of audio signal of collection, comprising:
N number of microphone is placed in test room, loudspeaker, N number of microphone are configured in the test room
Positioned at the front of the loudspeaker；
It controls the loudspeaker and plays white Gaussian noise data or swept-frequency signal data, and control N number of microphone point
N number of audio signal is not acquired.
22. according to the method for claim 21, which is characterized in that there is noise reduction room environmental in the test room, it is described
Loudspeaker is audio-frequency test Special artificial mouth, and the artificial mouth is calibrated with standard microphone before the use.
23. the method according to claim 21 or 22, which is characterized in that play white Gaussian noise controlling the loudspeaker
Before data or swept-frequency signal data, the method also includes:
Under quiet environment, N number of microphone is obtained in the first duration T1First audio data X of interior acquisition1(n)；
In the environment of playing white Gaussian noise data or swept-frequency signal data, N number of microphone is obtained in the second duration T2
The second audio data X of interior acquisition2(n)；
According to formulaSignal to Noise Ratio (SNR) is calculated, and ensures that the SNR is greater than first threshold.
24. a kind of equipment for assessing microphone array consistency characterized by comprising
Acquiring unit, the N number of audio signal acquired respectively for obtaining N number of microphone, N number of microphone constitute microphone array
Column, N >=2；
Processing unit, for determining every in addition to reference microphone in N number of microphone according to N number of audio signal
Phase spectrum difference and/or power spectrum difference between a microphone and the reference microphone, the reference microphone are the N
Any one microphone in a microphone；
The processing unit, be also used to according in N number of microphone in addition to the reference microphone each microphone with
Phase spectrum difference and/or power spectrum difference between the reference microphone carry out compliance evaluation to N number of microphone.
25. equipment according to claim 24, which is characterized in that the processing unit is specifically used for:
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Phase spectrum difference assesses the phase equalization between corresponding microphone and the reference microphone.
26. equipment according to claim 25, which is characterized in that the processing unit is also used to:
Each microphone in N number of microphone in addition to the reference microphone is measured respectively to arrive with the reference microphone
The range difference of sound source；
According to measured range difference, each Mike in N number of microphone in addition to the reference microphone is calculated separately
Fixed skew between wind and the reference microphone；
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Fixed skew calibrates its corresponding phase spectrum difference respectively.
27. equipment according to claim 26, which is characterized in that the processing unit is specifically used for:
According to formulaIt calculates separately in N number of microphone in addition to the reference microphone
Fixed skew between each microphone and the reference microphone,
Wherein, Yi(ω) indicates the frequency spectrum of i-th of microphone, Y1(ω) indicates that the frequency spectrum of reference microphone, ω indicate frequency, di
Indicate the range difference of i-th of microphone and reference microphone to sound source, the c expression velocity of sound, 2 π ω di/ c indicate i-th microphone with
Fixed skew between reference microphone.
28. the equipment according to any one of claim 24 to 27, which is characterized in that the processing unit is specifically used for:
According to each microphone in N number of microphone in addition to the reference microphone and between the reference microphone
Power spectrum difference assesses the amplitude coincidence between corresponding microphone and the reference microphone.
29. the equipment according to any one of claim 25 to 27, which is characterized in that N number of audio signal is to broadcast
Put the signal acquired in the environment of swept-frequency signal data.
30. equipment according to claim 28, which is characterized in that N number of audio signal is to play white Gaussian noise
The signal acquired in the environment of data or swept-frequency signal data.
31. the equipment according to claim 29 or 30, which is characterized in that the swept-frequency signal is Linear chirp, right
Number swept-frequency signals, linear stepping swept-frequency signal, any one in logarithm stepping swept-frequency signal.
32. the equipment according to any one of claim 24 to 31, which is characterized in that the processing unit is specifically used for:
Each audio signal in N number of audio signal is subjected to framing, obtains K signal frame of equal length, K >=2；
Windowing process is done to each signal frame in the K signal frame, obtains K windowing signal frame；
FFT transform is done to each windowing signal frame in the K windowing signal frame, obtains K echo signal frame；
According to the corresponding K echo signal frame of each audio signal, determine in N number of microphone except the reference
The phase spectrum difference and/or power spectrum difference between each microphone and the reference microphone except microphone.
33. equipment according to claim 32, which is characterized in that any two adjacent signals frame in the K signal frame
It is overlapped R%, R > 0.
34. equipment according to claim 33, which is characterized in that the R is 25 or 50.
35. the equipment according to any one of claim 32 to 34, which is characterized in that divided i-th of audio signal
Frame, K signal frame for obtaining equal length are write as following vector form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) i-th of audio signal is indicated, K indicates that each microphone collects the totalframes of signal, []TIndicate vector
Or the transposition of matrix.
36. the equipment according to any one of claim 32 to 35, which is characterized in that the processing unit is specifically used for:
According to formulaIt determines in N number of microphone in addition to the reference microphone
Each microphone and the reference microphone between phase spectrum difference,
Wherein, imag () expression takes imaginary part, and ln () expression takes natural logrithm,It indicates i-th of microphone and refers to wheat
Phase spectrum difference between gram wind,Indicate j-th of echo signal frame of reference microphone,Indicate i-th of wheat
J-th of echo signal frame of gram wind,Indicate basic frequency.
37. the equipment according to any one of claim 32 to 36, which is characterized in that the processing unit is specifically used for:
According to the corresponding K echo signal frame of each audio signal, the power spectrum of each audio signal is determined；
According to the power spectrum of each audio signal, determine every in addition to the reference microphone in N number of microphone
Power spectrum difference between a microphone and the reference microphone.
38. the equipment according to claim 37, which is characterized in that the processing unit is specifically used for:
According to formulaThe power spectrum of each audio signal is calculated,
Wherein, Pi(ω) indicates the power spectrum of i-th of audio signal, Yi,j(ω) indicates j-th of target in i-th of audio signal
Signal frame, K indicate that each microphone collects the totalframes of signal, and ω indicates frequency.
39. the equipment according to claim 37 or 38, which is characterized in that the processing unit is specifically used for:
According to formula PDi(ω)=P1(ω)-Pi(ω) calculates each wheat in N number of microphone in addition to reference microphone
Power spectrum difference gram between wind and the reference microphone,
Wherein, PDi(ω) indicates the power spectrum difference between i-th of microphone and reference microphone, P1(ω) indicates to refer to Mike
The power spectrum of wind, Pi(ω) indicates the power spectrum of i-th of microphone.
40. the equipment according to any one of claim 24 to 39, which is characterized in that the processing unit is specifically used for:
Determine sample frequency F of the N number of microphone when carrying out audio signal samplesWith FFT points Nfft, broadcast using loudspeaker
White Gaussian noise data or swept-frequency signal data are put, N number of microphone is controlled and acquires N number of audio signal, wherein if
The data that the loudspeaker is played are swept-frequency signal data, the swept-frequency signal data are equal by M+1 segment length and frequency not
Deng signal constitute,
41. equipment according to claim 40, which is characterized in that the processing unit is also used to:
According to formulaThe frequency of every segment signal in the M+1 segment signal is calculated, and
According to formula Si(t)=sin (2 π fiT) every segment signal in the M+1 segment signal is calculated,
Wherein, fiIndicate the frequency of the i-th segment signal, FsIndicate sample frequency, NfftIndicate FFT points, Si(t) i-th section of letter is indicated
Number, and S1(t) length is the integral multiple of cycle T, T=1/f1。
42. equipment according to claim 41, which is characterized in that the swept-frequency signal data that the loudspeaker is played are write as
Following vector form:
S (t)=[S0(t),S1(t),…,SM(t)]T
Wherein, S (t) indicates the swept-frequency signal data that loudspeaker is played, Si(t) the i-th segment signal is indicated,[]TTable
Show the transposition of vector or matrix.
43. the equipment according to any one of claim 24 to 42, which is characterized in that N number of microphone acquires respectively
To N number of audio signal, wherein the collected audio signal of i-th of microphone is expressed as xiAnd x (t),i(t) can be write as it is following to
Amount form:
xi(t)=[xi,1(t),xi,2(t),…,xi,K(t)]T
Wherein, xi(t) the collected audio signal of i-th of microphone is indicated, K indicates that each microphone collects total frame of signal
Number, []TIndicate the transposition of vector or matrix.
44. the equipment according to any one of claim 24 to 43, which is characterized in that the acquiring unit is specifically used for:
N number of microphone is placed in test room, loudspeaker, N number of microphone are configured in the test room
Positioned at the front of the loudspeaker；
It controls the loudspeaker and plays white Gaussian noise data or swept-frequency signal data, and control N number of microphone point
N number of audio signal is not acquired.
45. equipment according to claim 44, which is characterized in that there is noise reduction room environmental in the test room, it is described
Loudspeaker is audio-frequency test Special artificial mouth, and the artificial mouth is calibrated with standard microphone before the use.
46. the equipment according to claim 44 or 45, which is characterized in that control the loudspeaker in the processing unit and broadcast
Before putting white Gaussian noise data or swept-frequency signal data, the acquiring unit is also used to:
Under quiet environment, N number of microphone is obtained in the first duration T1First audio data X of interior acquisition1(n)；
In the environment of playing white Gaussian noise data or swept-frequency signal data, N number of microphone is obtained in the second duration T2
The second audio data X of interior acquisition2(n)；
The processing unit is triggered according to formulaSignal to Noise Ratio (SNR) is calculated, and ensures that the SNR is big
In first threshold.
47. a kind of device for assessing microphone array consistency characterized by comprising
Memory, for storing program and data；And
Processor, for calling and running the program and data that store in the memory；
Described device is configured as: executing the method as described in any one of claim 1 to 23.
48. a kind of system for assessing microphone array consistency characterized by comprising
Constitute N number of microphone of microphone array, N >=2；
At least one audio-source；
Device, including the memory for storing program and data and for calling and running the program stored in the memory
With the processor of data, described device is configured as:
Execute the method as described in any one of claim 1 to 23.
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| CN110111807A (en) * | 2019-04-27 | 2019-08-09 | 南京理工大学 | A kind of indoor sound source based on microphone array follows and Enhancement Method |
| CN110111807B (en) * | 2019-04-27 | 2022-01-11 | 南京理工大学 | Microphone array-based indoor sound source following and enhancing method |
| CN110636432A (en) * | 2019-09-29 | 2019-12-31 | 深圳市火乐科技发展有限公司 | Microphone testing method and related equipment |
| CN111065036B (en) * | 2019-12-26 | 2021-08-31 | 北京声智科技有限公司 | Frequency response testing method and device of microphone array |
| CN111065036A (en) * | 2019-12-26 | 2020-04-24 | 北京声智科技有限公司 | Frequency response testing method and device of microphone array |
| CN112672265A (en) * | 2020-10-13 | 2021-04-16 | 珠海市杰理科技股份有限公司 | Method and system for detecting microphone consistency and computer readable storage medium |
| CN112889299A (en) * | 2021-01-12 | 2021-06-01 | 华为技术有限公司 | Method and apparatus for evaluating microphone array consistency |
| WO2022150950A1 (en) * | 2021-01-12 | 2022-07-21 | 华为技术有限公司 | Method and apparatus for evaluating consistency of microphone array |
| CN113259830A (en) * | 2021-04-26 | 2021-08-13 | 歌尔股份有限公司 | Multi-microphone consistency test system and method |
| CN114390421A (en) * | 2021-12-03 | 2022-04-22 | 伟创力电子技术(苏州)有限公司 | Automatic testing method for microphone matrix and loudspeaker |
| CN114222234A (en) * | 2021-12-31 | 2022-03-22 | 思必驰科技股份有限公司 | Microphone array consistency detection method, electronic device and storage medium |
| CN114449434A (en) * | 2022-04-07 | 2022-05-06 | 荣耀终端有限公司 | Microphone calibration method and electronic equipment |
| CN115776626A (en) * | 2023-02-10 | 2023-03-10 | 杭州兆华电子股份有限公司 | Frequency response calibration method and system of microphone array |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109313909B (en) | 2023-05-12 |
| CN116437280A (en) | 2023-07-14 |
| WO2020037555A1 (en) | 2020-02-27 |
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