CN106128471B - A kind of contraction variable step subband acoustic echo removing method - Google Patents
A kind of contraction variable step subband acoustic echo removing method Download PDFInfo
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- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
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- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
- G10L21/0216—Noise filtering characterised by the method used for estimating noise
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- G—PHYSICS
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
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Abstract
A kind of contraction variable step subband acoustic echo removing method, the steps include: the sampling and processing of A, signal, and input vector U (n) is divided into I distal end subband vector U through analysis filter onei(n), the near end signal d (n) that proximal end microphone picks up is divided into I proximal end subband signal d through analysis filter twoi(n)；By distal end input subband vector Ui(n) I extraction is carried out through withdrawal device；It obtains distal end input subband and extracts vector Ui(k)；Equally, also to proximal end subband signal di(n) I is carried out through withdrawal device to extract to obtain proximal end subband extraction signal di(k), distal end input subband is extracted vector U by the output of B, filteri(k) sub-filter in filter is eliminated by adaptive echo and obtains output subband signal yi(k), C, echo cancelltion, the update of D, weight coefficient vector obtain the update step size mu of the weight coefficient vector of sub-filter based on denoising near end signal square estimatori(k), E, the step of enabling k=k+1, repeating A, B, C, D, until end of conversation.This method can obtain faster convergence rate and lower steady-state error.
Description
Technical field
The invention belongs to the adaptive echo technology for eliminating fields of voice communication.
Background technique
Currently, Echo Canceller is exactly to pass through core component-sef-adapting filter to carry out estimated echo, and near end signal
In subtract the estimated value of echo to achieve the effect that echo cancellor.Adaptive echo technology for eliminating is obtained because its is at low cost, effect is good
Approve to consistent, and one of the most promising echo cancellation technology generally acknowledged in the world at present.
In terms of the basic principle of echo cancellor, echo cancellor is realized using acoustic echo canceller, wherein most crucial
Part is exactly sef-adapting filter.Most common lowest mean square (LMS) algorithm is often in echo cancellation application in Adaptable System
In cannot obtain preferable effect.For this purpose, be suggested to solve this difficult point normalization Subband adaptive filters method, it should
Filter by frequency is divided into multiple subband signals by analysis by input signal for kind of method, the frequency due to input signal with return
The degree of correlation of sound is high, the echo cancellor different to the progress that different subband signals is adaptive, then is normalized, can be from
The difficulty for reducing echo cancellor on the whole, it is hereby achieved that preferable convergence rate.It is answered in current adaptive echo elimination
In, more mature sub-band approach is the adaptive filter algorithm for normalizing subband class, if any 1 " Variable of document
Regularisation parameter sign subband adaptive filter " (J.Ni and F.Li,
Electron.Lett., vol.46, no.24, pp.1605-1607, Nov.2010.) (SSAF) method, this method is will to accord with
Work song band (SSAF) algorithm, which is added, becomes regularization parameter strategy, reduces influence of the fixed step size to convergence rate and steady-state error,
This kind of method is versiera variable step, and step change is only with time correlation, and the time is longer, step-length is smaller；Therefore, in application bar
In the case that part changes or application conditions generation is unstable, the performance of algorithm can be reduced.
Summary of the invention
The object of the invention is to propose a kind of contraction variable step symbol subband acoustic echo removing method, this method carries out echo
It eliminates, faster convergence rate and lower steady-state error can be obtained.
The technical scheme adopted by the invention for realizing the object of the invention is a kind of contraction variable step subband acoustic echo elimination side
Method, its step are as follows:
A kind of contraction variable step subband acoustic echo removing method, its step are as follows:
A, the sampling and processing of signal
By the sampling remote signaling between current time n to moment n-L+1, current time n analysis filter one is constituted
Input vector U (n), U (n)=[u (n), u (n-1) ..., u (n-L+1)]T；L=512 is filter tap number, and subscript T is indicated
Transposition operation；
Input vector U (n) is divided into I distal end subband vector U through analysis filter onei(n), Ui(n)=[ui(n),ui
(n-1),...,ui(n-L+1)]T；
Meanwhile the near end signal d (n) with echo for the current time n for picking up proximal end microphone is through analysis filter
Two are divided into I proximal end subband signal di(n)；
Wherein, i is the serial number of distal end subband vector or proximal end subband signal, and i=1,2 ..., I, I are distal end subband vector
Or the total number of proximal end subband signal；
By distal end input subband vector Ui(n) I extraction is carried out through withdrawal device；The distal end at n=k=KI moment is inputted into son
Band vector Ui(n) it extracts out, obtains distal end input subband and extract vector Ui(k),Ui(k)=[ui(kI),ui(kI-1),...,ui
(kI-L+1)]T；Equally, also to proximal end subband signal di(n) I is carried out through withdrawal device to extract to obtain proximal end subband extraction signal di
(k), di(k)=di(KI)；Wherein, K is the serial number extracted, and k is the extraction moment that kth extracts；
B, the output of filter
Distal end input subband is extracted into vector Ui(k) sub-filter in filter is eliminated by adaptive echo to obtain
Output subband signal yi(k),Wherein W (k) is sub-filter in the weight coefficient for extracting moment k
Vector, W (k)=[w1(k),w2(k),..wl(k).,wL(k)]T；wlIt (k) is first of weight coefficient in weight coefficient vector W (k), l
=1,2 ..., L is weight coefficient wl(k) serial number；The initial value of W (k) is zero, i.e. W (1)=0；
C, echo cancelltion
Nearly terminal band extracts signal di(k) with output subband signal yi(k) subtract each other to obtain error signal ei(k), that is, it eliminates
Near end signal e after echoi(k), ei(k)=di(k)-yi(k), and by near end signal ei(k) distal end is sent back to；
D, the update of weight coefficient vector
D1, according near end signal ei(k) the near end signal square estimator for extracting moment k is calculated
Wherein τ1Indicate the smoothing parameter of near end signal square estimator, value 0.2；Median () expression takes middle position
Number operation；Initial value be zero, i.e.,M is the size for the smooth window that near end signal square is smoothly estimated,
Value is 10~20；
D2, the restriction parameter for calculating near end signal square estimator
IfThenWhereinTo prevent the regularization that denominator is zero
Parameter, value 0.001.
IfThen
D3, according to limit parameterCalculate the denoising near end signal for extracting moment k
IfThen
IfThenWherein sign () indicates symbol
It calculates；
D4, according to denoising near end signalCalculate the denoising near end signal square estimator for extracting moment k
WhereinInitial value be zero, i.e.,τ2Indicate denoising proximal end estimator smoothing parameter, value is
0.2；
D5, the update step size mu for extracting the weight coefficient vector of moment k is calculatedi(k),And then more
Next weight coefficient vector W (k+1) for extracting moment k+1 is newly obtained,
E, the step of enabling k=k+1, repeating A, B, C, D, until end of conversation.
Compared with prior art, the beneficial effects of the present invention are:
Update step size mu of the inventioni(k) calculating formula isThat is, the present invention is by smoothly joining
Number estimation method obtains the median of the near end signal square in a smoothingtime section, as near end signal square estimator,
Method is limited by parameter again and obtains denoising near end signal square estimator, finally denoises near end signal square estimator divided by close
The square root of end signal square estimator and multiplied by a constantObtain the update of the weight coefficient vector of sub-filter
Step size mui(k).When denoising near end signal (denoising error signal) greatly namely when algorithm is not up to stable state, step-length of the invention
Greatly, so as to obtaining cracking convergence rate；When reaching stable state, denoising near end signal square estimator is small, is calculated
Step-length it is also small, therefore, the steady-state error of the available very little of algorithm.
In short, method of the invention can obtain big step-length, to restrain quickly as long as algorithm deviates stable state；Simultaneously only
Want algorithm to reach stable state, small step-length can be obtained, realize the steady-state error of very little, so as to changing in application conditions or
In the case that application conditions are unstable, guarantee that system has good echo cancellation performance.
The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments
Detailed description of the invention
Fig. 1 is the channel mapping of emulation experiment of the present invention.
Fig. 2 is SSAF method and the present invention when actual speech signal is input signal, the normalization stable state of emulation experiment
Imbalance curve.
Specific embodiment
Embodiment
A kind of specific embodiment of the invention is:
A kind of contraction variable step subband acoustic echo removing method, its step are as follows:
A kind of contraction variable step subband acoustic echo removing method, its step are as follows:
A, the sampling and processing of signal
By the sampling remote signaling between current time n to moment n-L+1, current time n analysis filter one is constituted
Input vector U (n), U (n)=[u (n), u (n-1) ..., u (n-L+1)]T；L=512 is filter tap number, and subscript T is indicated
Transposition operation；
Input vector U (n) is divided into I distal end subband vector U through analysis filter onei(n), Ui(n)=[ui(n),ui
(n-1),...,ui(n-L+1)]T；
Meanwhile the near end signal d (n) with echo for the current time n for picking up proximal end microphone is through analysis filter
Two are divided into I proximal end subband signal di(n)；
Wherein, i is the serial number of distal end subband vector or proximal end subband signal, and i=1,2 ..., I, I are distal end subband vector
Or the total number of proximal end subband signal；
By distal end input subband vector Ui(n) I extraction is carried out through withdrawal device；The distal end at n=k=KI moment is inputted into son
Band vector Ui(n) it extracts out, obtains distal end input subband and extract vector Ui(k),Ui(k)=[ui(kI),ui(kI-1),...,ui
(kI-L+1)]T；Equally, also to proximal end subband signal di(n) I is carried out through withdrawal device to extract to obtain proximal end subband extraction signal di
(k), di(k)=di(KI)；Wherein, K is the serial number extracted, and k is the extraction moment that kth extracts；
B, the output of filter
Distal end input subband is extracted into vector Ui(k) sub-filter in filter is eliminated by adaptive echo to obtain
Output subband signal yi(k),Wherein W (k) is sub-filter in the weight coefficient for extracting moment k
Vector, W (k)=[w1(k),w2(k),..wl(k).,wL(k)]T；wlIt (k) is first of weight coefficient in weight coefficient vector W (k), l
=1,2 ..., L is weight coefficient wl(k) serial number；The initial value of W (k) is zero, i.e. W (1)=0；
C, echo cancelltion
Nearly terminal band extracts signal di(k) with output subband signal yi(k) subtract each other to obtain error signal ei(k), that is, it eliminates
Near end signal e after echoi(k), ei(k)=di(k)-yi(k), and by near end signal ei(k) distal end is sent back to；
D, the update of weight coefficient vector
D1, according near end signal ei(k) the near end signal square estimator for extracting moment k is calculated
Wherein τ1Indicate the smoothing parameter of near end signal square estimator, value 0.2；Median () expression takes middle position
Number operation；Initial value be zero, i.e.,M is the size for the smooth window that near end signal square is smoothly estimated,
Value is 10~20；
D2, the restriction parameter for calculating near end signal square estimator
IfThenWhereinTo prevent the regularization that denominator is zero
Parameter, value 0.001.
IfThen
D3, according to limit parameterCalculate the denoising near end signal for extracting moment k
IfThen
IfThenWherein sign () indicates symbol
It calculates；
D4, according to denoising near end signalCalculate the denoising near end signal square estimator for extracting moment k
WhereinInitial value be zero, i.e.,τ2Indicate denoising proximal end estimator smoothing parameter, value is
0.2；
D5, the update step size mu for extracting the weight coefficient vector of moment k is calculatedi(k),
And then update and obtain next weight coefficient vector W (k+1) for extracting moment k+1,
E, the step of enabling k=k+1, repeating A, B, C, D, until end of conversation.
Emulation experiment
In order to verify effectiveness of the invention, emulation experiment has been carried out, and carried out pair with the method for existing document 1
Than.
The sample frequency of emulation experiment is 8KHz.Ambient noise is the zero mean Gaussian white noise of 30dB signal-to-noise ratio.Echo
Channel impulse response is in long 6.25m, wide 3.75m, high 2.5m, and 20 DEG C of temperature, the quiet closed room of humidity 50% is interior to be obtained, arteries and veins
Rush the tap number L=512 of the i.e. filter of response length.
According to the above experiment condition, echo cancellor experiment is carried out with the method for the present invention and existing one method of document.It is various
The experiment optimized parameter value such as table 1 of method.
The experiment optimized parameter value of 1 each method of table
| Document one (SSAF) | κ=0；ε=0.0001；δ=0.01；N=4 |
| The present invention | fl(0)=0.001；δ=0.01；N=4 |
Fig. 1 is the channel mapping for the communication system that the quiet closed room of experiment is constituted.
Fig. 2 is the method and the method for the present invention of document one (SSAF), and when actual speech signal is input signal, emulation is real
The normalization steady output rate curve tested.
As can be seen from Figure 2: the present invention is restrained in about 7000 sampling instants (0.8s), and steady-state error is about in -40dB；And
Document 1 is then restrained in about 20000 sampling instants (2.5s), and steady-state error is about in -25dB；The present invention is than 1 convergence rate of document
Fast twice or more, steady-state error reduces nearly twice.
Claims (1)
1. a kind of contraction variable step subband acoustic echo removing method, its step are as follows:
A, the sampling and processing of signal
By the sampling remote signaling between current time n to moment n-L+1, the input of current time n analysis filter one is constituted
Vector U (n), U (n)=[u (n), u (n-1) ..., u (n-L+1)]T；L=512 is filter tap number, and subscript T indicates transposition
Operation；
Input vector U (n) is divided into I distal end subband vector U through analysis filter onei(n), Ui(n)=[ui(n),ui(n-
1),...,ui(n-L+1)]T；
Meanwhile the near end signal d (n) with echo for the current time n that proximal end microphone picks up being divided through analysis filter two
It is cut into I proximal end subband signal di(n)；
Wherein, i is the serial number of distal end subband vector or proximal end subband signal, and i=1,2 ..., I, I are for distal end subband vector or closely
The total number of terminal band signal；
By distal end input subband vector Ui(n) I extraction is carried out through withdrawal device；I.e. by the distal end input subband at n=k=KI moment to
Measure Ui(n) it extracts out, obtains distal end input subband and extract vector Ui(k),Ui(k)=[ui(KI),ui(KI-1),...,ui(KI-L+
1)]T；Equally, also to proximal end subband signal di(n) I is carried out through withdrawal device to extract to obtain proximal end subband extraction signal di(k), di
(k)=di(KI)；Wherein, K is the serial number extracted, and k is the extraction moment that kth extracts；
B, the output of filter
Distal end input subband is extracted into vector Ui(k) sub-filter in filter is eliminated by adaptive echo to be exported
Subband signal yi(k),Wherein W (k) is weight coefficient vector of the sub-filter in extraction moment k,
W (k)=[w1(k),w2(k),..wl(k).,wL(k)]T；wlIt (k) is first of weight coefficient in weight coefficient vector W (k), l=1,
2 ..., L is weight coefficient wl(k) serial number；The initial value of W (k) is zero, i.e. W (1)=0；
C, echo cancelltion
Nearly terminal band extracts signal di(k) with output subband signal yi(k) subtract each other to obtain error signal ei(k), that is, echo is eliminated
Near end signal e afterwardsi(k), ei(k)=di(k)-yi(k), and by near end signal ei(k) distal end is sent back to；
D, the update of weight coefficient vector
D1, according near end signal ei(k) the near end signal square estimator for extracting moment k is calculated
Wherein τ1Indicate the smoothing parameter of near end signal square estimator, value 0.2；Median () expression takes median to transport
It calculates；Initial value be zero, i.e.,M is the size for the smooth window that near end signal square is smoothly estimated, value
It is 10~20；
D2, the restriction parameter for calculating near end signal square estimator
IfThenWherein θ is the regularization parameter for preventing denominator from being zero,
Value is 0.001；
IfThen
D3, according to limit parameterCalculate the denoising near end signal for extracting moment k
IfThen
IfThenWherein sign () indicates sign computation；
D4, according to denoising near end signalCalculate the denoising near end signal square estimator for extracting moment k
WhereinInitial value be zero, i.e.,τ2Indicate denoising proximal end estimator smoothing parameter, value 0.2；
D5, the update step size mu for extracting the weight coefficient vector of moment k is calculatedi(k),And then it updates and obtains
Next weight coefficient vector W (k+1) for extracting moment k+1,
E, the step of enabling k=k+1, repeating A, B, C, D, until end of conversation.
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| CN107291663A (en) * | 2017-06-12 | 2017-10-24 | 华侨大学 | The variable step suppressed applied to acoustic feedback normalizes sub-band adaptive filtering method |
| CN111028856B (en) * | 2020-01-08 | 2022-01-28 | 西南交通大学 | Echo cancellation method with variable step length |
| CN112132104B (en) * | 2020-10-09 | 2021-08-03 | 哈尔滨工业大学 | ISAR ship target image domain enhancement identification method based on loop generation countermeasure network |
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