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CN111916099A - Adaptive echo cancellation device and method for variable-step hearing aid - Google Patents

Adaptive echo cancellation device and method for variable-step hearing aid Download PDF

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CN111916099A
CN111916099A CN202011090523.1A CN202011090523A CN111916099A CN 111916099 A CN111916099 A CN 111916099A CN 202011090523 A CN202011090523 A CN 202011090523A CN 111916099 A CN111916099 A CN 111916099A
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normalized
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step length
energy
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CN111916099B (en
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徐佳利
孟宪军
钱晓峰
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Nanjing Tianyue Electronic Technology Co ltd
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • 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
    • G10L21/0208—Noise filtering
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • 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
    • G10L21/0208—Noise filtering
    • G10L2021/02082—Noise filtering the noise being echo, reverberation of the speech

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Abstract

The invention discloses a self-adaptive echo cancellation device and a self-adaptive echo cancellation method for a variable-step-size hearing aid, wherein the self-adaptive echo cancellation device comprises a single-frequency tone detector, a step-size controller and a self-adaptive filter: the single-frequency tone detector is used for carrying out spectrum energy analysis on the error signal sample, calculating the current state parameter of the hearing aid system and transmitting the parameter to the step length controller; the step length controller is used for judging the state of the system according to the system state parameters and the normalized error mean value obtained from the single-frequency tone detector, calculating the time-varying step length parameters of the self-adaptive filter and transmitting the time-varying step length parameters to the self-adaptive filter; the self-adaptive filter is used for filtering the cached far-end signal sample of the loudspeaker, calculating and estimating an echo signal and then outputting the echo signal, and iteratively updating the self-adaptive filter according to the time-varying step length parameter calculated by the step length controller. The method solves the problems that the self-adaptive filter in the prior art is low in convergence speed and high in algorithm complexity and is difficult to realize, and is suitable for a digital hearing aid system.

Description

Adaptive echo cancellation device and method for variable-step hearing aid
Technical Field
The invention relates to a step-size-variable hearing aid self-adaptive echo cancellation device and a step-size-variable hearing aid self-adaptive echo cancellation method.
Background
With the development of industrialization and the increasing aging of recent years, the number of people suffering from hearing loss diseases is continuously increasing, and the selection of hearing aids to improve hearing loss is the most common and quick auxiliary means. However, the hearing aid has a very easy structure and function to amplify echo and generate howling, so the echo cancellation algorithm is one of the key algorithms of the digital hearing aid, which estimates the echo signal by estimating the characteristic parameters of the echo path, using the far-end signal of the loudspeaker as a reference, and then estimates the echo signal from the received near-end microphone signal. Since the echo path is usually unknown and time-varying, especially since slight wear adjustments during use of the hearing aid change the echo path, the adaptive filter becomes a key component of the hearing aid echo cancellation module by virtue of its ability to track the time-varying system.
The patent with publication number CN101179294B discloses an adaptive echo canceller and an echo cancellation method thereof, and as described in the background of paragraph [0011] of the present application, "in an embedded system, an adaptive algorithm commonly used in an echo canceller is an algorithm group based on the steepest descent method. A representation of such an adaptive algorithm is: LMS (least mean square error) algorithm whose minimization criterion is the root mean square error. The self-adaptive algorithm has the advantages of small calculation amount, strong robustness and easy realization, and is widely adopted in practice. The disadvantages are: the convergence speed is slow and the convergence performance is sensitive to energy variations of the input signal. The NLMS (energy normalized least mean square error) algorithm is an improved algorithm of the LMS algorithm and overcomes the defect that the LMS algorithm is sensitive to the energy of an input signal. The NLMS algorithm and its various modifications are the adaptive filtering algorithm in echo cancellers that are mainly used at present.
Taking an adaptive algorithm LMS as an example, in the adaptive process of the filter, in practical situations, especially in the field of hearing aids, noise or voice signals inevitably exist in the near-end signal except for the desired signal, and the noise equivalent to the noise added with a large signal greatly affects the convergence rate of the adaptive process and may cause divergence in severe cases, and this condition is called double-ended sounding (DT) in the hearing aid echo cancellation system. The misadjustment of the self-adaptation process of the filter can be slowed down to a certain extent by directly reducing the convergence step size parameter, however, the convergence speed of the algorithm and the tracking speed of the time-varying system can be seriously reduced, and the calculation difficulty in the fixed-point system can be caused by the too small step size parameter.
Some echo cancellation algorithms include a double talk detection module (DTD): the double talk detection is to determine the talk state of the current system (near-end talk, far-end talk, double-end talk), when the system is determined to be double-end talk, the adaptive filter does not update the coefficient, and the general DTD method has a disadvantage that the method cannot adapt to the characteristic that the echo path in the echo cancellation environment is changed continuously. Therefore, many scholars have actively studied the existing problems in the adaptive filter echo cancellation method and have proposed many improvements. The method mainly comprises the steps of giving a variable step function or analyzing an input end signal and the like to control the updating of the coefficient of the adaptive filter so as to improve the stable initial convergence speed and the stable error of an echo path. However, these methods generally have the problems of high requirement on computational accuracy and high computational complexity, and are difficult to implement in a hearing aid echo cancellation system, and in the prior art, there is no method suitable for a hearing aid and considering power consumption and computational complexity, which can solve the above problems well.
Disclosure of Invention
Aiming at the problems, the invention provides a variable step length hearing aid self-adaptive echo cancellation device and an echo cancellation method, which solve the problems that the self-adaptive filter in the prior art is low in convergence speed and too high in algorithm complexity and difficult to realize; furthermore, the problems that the steady-state error of the self-adaptive filter is large, double-end sounding and parameter misadjustment can be caused by related data in the prior art are solved.
In order to achieve the technical purpose and achieve the technical effect, the invention is realized by the following technical scheme:
a step size-variable hearing aid adaptive echo cancellation device comprises a single-frequency tone detector, a step size controller and an adaptive filter:
the single tone detector is used for correcting error signals
Figure 868244DEST_PATH_IMAGE001
Carrying out spectrum energy analysis on the sample, calculating the current state parameter of the hearing aid system, and transmitting the parameter to the step length controller;
the step size controller is used for obtaining a normalized error mean value according to the system state parameters obtained from the single-frequency tone detector
Figure 725342DEST_PATH_IMAGE002
Judging the state of the system, and calculating the time-varying step length parameter of the adaptive filter
Figure 950787DEST_PATH_IMAGE003
And passes it to the adaptive filter;
the adaptive filter is used for buffering loudspeaker far-end signals
Figure 664665DEST_PATH_IMAGE004
Filtering the samples to calculate an estimated echo signal
Figure 178823DEST_PATH_IMAGE005
Then outputting, and carrying out iterative updating on the self-adaptive filter according to the time-varying step length parameter calculated by the step length controller;
wherein the error signal
Figure 105191DEST_PATH_IMAGE006
For near-end speech signals
Figure 716300DEST_PATH_IMAGE007
Subtracting the estimated echo signal
Figure 273184DEST_PATH_IMAGE005
；
Normalized mean of error
Figure 841349DEST_PATH_IMAGE008
Is an error signal
Figure 774670DEST_PATH_IMAGE006
Relative to the far-end signal
Figure 240287DEST_PATH_IMAGE004
Normalized long term average.
Preferably, the single-frequency tone detector includes a framing FFT module and a spectral energy analysis module:
the frame FFT module is used for receiving the buffered error signal
Figure 968071DEST_PATH_IMAGE006
For the error signal
Figure 519138DEST_PATH_IMAGE006
Performing fast Fourier transform according to a set frequency, calculating a power spectrum of the signal and transmitting the power spectrum to a spectrum energy analysis module;
the spectrum energy analysis module analyzes the maximum single-frequency energy of the obtained signal spectrum
Figure 990571DEST_PATH_IMAGE009
Ratio of maximum single-frequency energy to total energy of power spectrum
Figure 310694DEST_PATH_IMAGE010
And the obtained system state parameters are transmitted to the step size controller.
Preferably, the step length controller comprises a state selection module, and the state selection module selects the state of the system according to the system state parameters obtained by the single-frequency tone detector, and controls and adjusts the time-varying step length parameters
Figure 474959DEST_PATH_IMAGE011
Time-varying step size parameter
Figure 513322DEST_PATH_IMAGE011
To an adaptive filter.
Preferably, the step size controller corrects the coefficient according to the normalization
Figure 522866DEST_PATH_IMAGE012
And most obtained by single tone detectorLarge single frequency energy
Figure 963075DEST_PATH_IMAGE009
And the ratio of maximum single-frequency energy to total energy of power spectrum
Figure 32662DEST_PATH_IMAGE010
Judging the threshold value, and controlling and adjusting the time-varying step length parameter according to the judgment result
Figure 558321DEST_PATH_IMAGE011
The method specifically comprises the following steps:
1) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 371557DEST_PATH_IMAGE010
Less than a set threshold
Figure 666272DEST_PATH_IMAGE013
If yes, the system is judged to be in steady state convergence, and a preset steady state step length parameter is adopted
Figure 172339DEST_PATH_IMAGE014
As a time-varying step size parameter;
2) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 421180DEST_PATH_IMAGE010
Greater than a set threshold
Figure 38106DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 187328DEST_PATH_IMAGE009
Less than a set threshold
Figure 864297DEST_PATH_IMAGE015
If the system is determined to be in a related interference state, the normalization correction coefficient is used
Figure 98969DEST_PATH_IMAGE012
Correcting time-varying step size parameters：
Figure 50745DEST_PATH_IMAGE016
；
3) If the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 257735DEST_PATH_IMAGE010
Greater than a set threshold
Figure 167922DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 827574DEST_PATH_IMAGE009
Greater than a set threshold
Figure 848619DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 644537DEST_PATH_IMAGE012
Less than a set threshold
Figure 928888DEST_PATH_IMAGE017
If yes, the system is judged to be in a howling state, and at the moment, howling is preferentially processed, and a fixed step length parameter is adopted
Figure 138152DEST_PATH_IMAGE018
Filter iteration is accelerated:
Figure 900572DEST_PATH_IMAGE019
wherein
Figure 878892DEST_PATH_IMAGE020
；
4) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 802986DEST_PATH_IMAGE010
Greater than a set threshold
Figure 732503DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 95351DEST_PATH_IMAGE009
Greater than a set threshold
Figure 131440DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 288752DEST_PATH_IMAGE012
Greater than a set threshold
Figure 410291DEST_PATH_IMAGE017
If the system is in a double-end sounding state, the time-varying step length parameter is set to zero to stop the adaptive iteration of the filter
Figure 576831DEST_PATH_IMAGE021
。
Preferably, the adaptive filter includes a normalized error signal processing module, a coefficient updating module, and a FIR filter module:
the normalized error signal processing module is used for processing the error signal
Figure 201847DEST_PATH_IMAGE006
Far-end signal relative to loudspeaker
Figure 795639DEST_PATH_IMAGE004
Is normalized by the square of the Euclidean norm to obtain a normalized error signal
Figure 138896DEST_PATH_IMAGE022
；
Wherein,
Figure 109126DEST_PATH_IMAGE023
is the far-end signal vector for the corresponding time delay,
Figure 854228DEST_PATH_IMAGE024
in order to adapt the order of the filter,
Figure 618922DEST_PATH_IMAGE025
is a constant;
normalizing error signals according to set frequency by convex combination first-order recursion process
Figure 449475DEST_PATH_IMAGE026
Performing snapshot smoothing to obtain a normalized average error;
the coefficient updating module obtains time-varying step length parameters according to the normalized error signals, the normalized average errors and the step length controller
Figure 957816DEST_PATH_IMAGE011
Iteratively updating the adaptive filter coefficients;
the FIR filter module is used for far-end signal
Figure 557425DEST_PATH_IMAGE027
Filtering to obtain estimated echo signal
Figure 994485DEST_PATH_IMAGE005
And then outputting.
A variable step size hearing aid adaptive echo cancellation device according to any one of the preceding claims, adapted for use in a digital hearing aid system.
Correspondingly, the adaptive echo cancellation method for the variable-step hearing aid comprises the following steps:
A. according to the cached far-end signal sample, the estimated echo signal is obtained through filtering of a self-adaptive FIR filter
Figure 312334DEST_PATH_IMAGE005
：
Figure 358787DEST_PATH_IMAGE028
Wherein
Figure 78481DEST_PATH_IMAGE029
，
Figure 184978DEST_PATH_IMAGE030
is an FIR filter systemThe number of the first and second groups is,
Figure 990123DEST_PATH_IMAGE031
is composed of
Figure 840267DEST_PATH_IMAGE032
The conjugate transpose of (1); and the sampled near-end voice signal
Figure 414468DEST_PATH_IMAGE033
Subtracting the estimated echo signal
Figure 691865DEST_PATH_IMAGE005
To obtain an error signal
Figure 718727DEST_PATH_IMAGE034
；
B. Performing time-frequency transformation on the error signal, calculating the power spectrum of the error signal and analyzing the energy distribution characteristic to obtain system state parameters;
C. judging the state of the system according to the system state parameters, and controlling the self-adaptive time-varying step length parameters
Figure 372562DEST_PATH_IMAGE011
；
D. For error signal
Figure 801270DEST_PATH_IMAGE006
Far-end signal relative to loudspeaker
Figure 249569DEST_PATH_IMAGE004
The square of the Euclidean norm is normalized to obtain a normalized error mean value
Figure 29306DEST_PATH_IMAGE008
Carrying out smooth processing on the maximum value of each frame of the normalized error signal by using a convex combination first-order recursion process, and using the maximum value as an upper limit threshold value of the normalized adaptive error;
E. using modified time-varying step-size parameters
Figure 221253DEST_PATH_IMAGE011
And the normalized error iteratively updates the FIR filter coefficient:
Figure 504466DEST_PATH_IMAGE035
。
preferably, the step B specifically includes:
b1, continuously filling error signals into a buffer area of the single-frequency tone detector, performing one-time fast Fourier transform operation after the buffer area is full of data, resetting the buffer to obtain the frequency spectrum of the signals, and further calculating the power spectrum of the signals
Figure 881922DEST_PATH_IMAGE036
：
Figure 883376DEST_PATH_IMAGE037
Wherein
Figure 879014DEST_PATH_IMAGE038
as the number of frames,
Figure 16734DEST_PATH_IMAGE039
are the frequency points of the frequency,
Figure 72415DEST_PATH_IMAGE040
；
Figure 561165DEST_PATH_IMAGE041
is FFT operation;
Figure 94914DEST_PATH_IMAGE042
the number of fast Fourier transform points;
b2, finding the maximum energy frequency point according to the power spectrum of the signal
Figure 352720DEST_PATH_IMAGE044
Calculating the energy sum of the maximum energy frequency point and the adjacent frequency points
Figure 579302DEST_PATH_IMAGE009
：
Figure 289769DEST_PATH_IMAGE045
；
Calculating the ratio of the maximum single-frequency energy to the total energy of the power spectrum
Figure 627210DEST_PATH_IMAGE010
：
Figure 5101DEST_PATH_IMAGE046
；
Wherein,
Figure 137005DEST_PATH_IMAGE042
the number of fast Fourier transform points;
the state parameter is measured
Figure 600348DEST_PATH_IMAGE009
、
Figure 475900DEST_PATH_IMAGE010
To the step size controller.
Preferably, the step C specifically includes:
c1 maximum ratio of single-frequency energy to total energy of power spectrum obtained by single-frequency tone detector
Figure 740921DEST_PATH_IMAGE010
Smooth normalization correction coefficient
Figure 43727DEST_PATH_IMAGE012
：
Figure 994365DEST_PATH_IMAGE047
；
Wherein,
Figure 673608DEST_PATH_IMAGE048
a forgetting factor, a positive number less than 1;
Figure 760513DEST_PATH_IMAGE049
，
Figure 499799DEST_PATH_IMAGE050
for controlling correction coefficient
Figure 672154DEST_PATH_IMAGE012
Between 0 and 1;
Figure 889509DEST_PATH_IMAGE051
is a set threshold value;
c2 maximum single frequency energy
Figure 96499DEST_PATH_IMAGE009
Ratio of maximum single-frequency energy to total energy of power spectrum
Figure 741107DEST_PATH_IMAGE052
Normalized correction factor
Figure 400759DEST_PATH_IMAGE012
And judging a threshold value, and adjusting a time-varying step length parameter according to the judgment results of the three state parameters, specifically:
1) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 421804DEST_PATH_IMAGE010
Less than a set threshold
Figure 483301DEST_PATH_IMAGE013
If yes, the system is judged to be in steady state convergence, and a preset steady state step length parameter is adopted
Figure 564390DEST_PATH_IMAGE014
As a time-varying step size parameter;
2) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 711337DEST_PATH_IMAGE010
Greater than a set threshold
Figure 503451DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 481771DEST_PATH_IMAGE009
Less than a set threshold
Figure 671444DEST_PATH_IMAGE015
If the system is determined to be in a related interference state, the normalization correction coefficient is used
Figure 368004DEST_PATH_IMAGE012
Correcting time-varying step length parameters:
Figure 668536DEST_PATH_IMAGE016
；
3) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 501363DEST_PATH_IMAGE010
Greater than a set threshold
Figure 861937DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 45793DEST_PATH_IMAGE009
Greater than a set threshold
Figure 884436DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 837349DEST_PATH_IMAGE012
Less than a set threshold
Figure 368824DEST_PATH_IMAGE017
If yes, the system is judged to be in a howling state, and at the moment, howling is preferentially processed, and a fixed step length parameter is adopted
Figure 774398DEST_PATH_IMAGE018
Filter iteration is accelerated:
Figure 682311DEST_PATH_IMAGE019
wherein
Figure 489730DEST_PATH_IMAGE020
；
4) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 192107DEST_PATH_IMAGE010
Greater than a set threshold
Figure 586441DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 766887DEST_PATH_IMAGE009
Greater than a set threshold
Figure 694392DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 567670DEST_PATH_IMAGE012
Greater than a set threshold
Figure 947836DEST_PATH_IMAGE017
If so, judging that the system is in a double-end sounding state, and setting the time-varying step length parameter to zero at the moment to stop the adaptive iteration of the filter:
Figure 931972DEST_PATH_IMAGE021
。
preferably, the step D specifically includes:
d1, for the current error signal
Figure 713983DEST_PATH_IMAGE006
Far-end signal relative to loudspeaker
Figure 758163DEST_PATH_IMAGE004
Square of the euclidean norm of
Figure 625624DEST_PATH_IMAGE053
Normalization is performed to obtain a normalized error signal
Figure 413452DEST_PATH_IMAGE026
：
Figure 49970DEST_PATH_IMAGE022
；
Wherein,
Figure 265050DEST_PATH_IMAGE025
is a constant;
d2, calculating the absolute value of the normalized error signal of each frame
Figure 354229DEST_PATH_IMAGE054
Maximum value of
Figure 945747DEST_PATH_IMAGE055
And smoothing the data by convex combination first order recursion process to obtain normalized error mean of normalized error signal
Figure 436772DEST_PATH_IMAGE008
：
Figure 822754DEST_PATH_IMAGE056
；
Wherein,
Figure 169202DEST_PATH_IMAGE057
and
Figure 298832DEST_PATH_IMAGE058
is a forgetting factor;
d3, normalizing the normalized error mean of the error signal
Figure 644363DEST_PATH_IMAGE008
As the upper threshold limit for the error signal.
The invention has the beneficial effects that:
1) the invention takes the detection data of the single-frequency tone detector as the basis, and by means of the multiplier, FFT and other modules of the hearing aid chip, the algorithm is low in complexity and power consumption, is easy to realize in the digital hearing aid, and solves the problems that the self-adaptive filter in the prior art is low in convergence speed and high in algorithm complexity and is difficult to realize.
2) According to the method, the iteration step length is corrected according to the distribution characteristics of the frequency spectrum energy of the historical data after echo elimination to weaken the maladjustment problem caused by single-frequency noise, the working state of the adaptive filter is switched to quickly inhibit howling, good balance is achieved in the convergence speed and the steady-state error of the adaptive filter, and a time-varying system can be quickly tracked and howling inhibition can be quickly achieved.
3) The invention takes the long-term average value of the normalized error signal as the dynamic threshold value to control the iteration step length of the filter not to have sudden change, weakens the influence of double-end talkback under the conditions of higher robustness and faster convergence speed, and solves the problems of large steady-state error of the self-adaptive filter, double-end sounding, parameter imbalance generation of related data and the like in the prior art.
4) The adaptive filter has strong anti-interference capability in an external noise or double-end talkback scene, and can obviously prevent the iterative divergence of the adaptive filter. When the device is in an environment with strong noise single-frequency energy, the detuning can be effectively prevented.
Drawings
Fig. 1 is a block diagram of an adaptive echo cancellation device for a hearing aid with variable step size according to the present invention;
fig. 2 is a diagram comparing the convergence performance of the present method and the conventional method in the presence of external interference.
Detailed Description
The present invention will be better understood and implemented by those skilled in the art by the following detailed description of the technical solution of the present invention with reference to the accompanying drawings and specific examples, which are not intended to limit the present invention.
As shown in fig. 1, a step-size-variable hearing aid adaptive echo cancellation apparatus mainly includes a single-frequency tone detector, a step-size controller, and an adaptive filter, and specifically, the following components are mainly introduced:
the single tone detector is used for correcting error signals
Figure 466825DEST_PATH_IMAGE006
And carrying out spectrum energy analysis on the sample, calculating the current state parameter of the hearing aid system, and transmitting the parameter to the step size controller.
Adaptive echo cancellation device for external input signal
Figure 530596DEST_PATH_IMAGE059
Collecting to obtain near-end voice signal
Figure 198338DEST_PATH_IMAGE033
Wherein the error signal
Figure 663954DEST_PATH_IMAGE006
For near-end speech signals
Figure 657318DEST_PATH_IMAGE060
Subtracting the estimated echo signal
Figure 942806DEST_PATH_IMAGE061
。
The step size controller is used for obtaining a normalized error mean value according to the system state parameters obtained from the single-frequency tone detector
Figure 679818DEST_PATH_IMAGE008
Judging the state of the system, and calculating the time-varying step length parameter of the adaptive filter
Figure 999941DEST_PATH_IMAGE011
And passes it to the adaptive filter. Wherein the error mean is normalized
Figure 898627DEST_PATH_IMAGE008
Is an error signal
Figure 936990DEST_PATH_IMAGE006
Relative to the far-end signal
Figure 212113DEST_PATH_IMAGE062
Normalized long term average.
The adaptive filter is used for buffering loudspeaker far-end signals
Figure 386743DEST_PATH_IMAGE004
Filtering the samples to calculate an estimated echo signal
Figure 721909DEST_PATH_IMAGE005
And then outputting, and carrying out iterative updating on the self-adaptive filter according to the time-varying step length parameter calculated by the step length controller. In the filtering process, the time-varying step size parameter updated last time is adopted for filtering, and the time-varying step size parameter updated this time is used for the next filtering process, so that the operation can be reduced, the power consumption of the hearing aid is reduced, and the implementation in the digital hearing aid is easier.
Preferably, the main structure and function of each component of the adaptive echo cancellation device are described as follows:
preferably, the single-frequency tone detector includes a framing FFT module and a spectral energy analysis module, wherein:
the frame FFT module is used for receiving the buffered error signal
Figure 483454DEST_PATH_IMAGE006
For the error signal
Figure 562268DEST_PATH_IMAGE006
Performing Fast Fourier Transform (FFT) according to a set frequency, calculating a power spectrum of the signal and transmitting the power spectrum to a spectrum energy analysis module;
the spectrum energy analysis module analyzes the maximum single-frequency energy of the obtained signal spectrum
Figure 856984DEST_PATH_IMAGE009
Maximum single frequency energyRatio of quantity to total energy of power spectrum
Figure 97472DEST_PATH_IMAGE010
And the obtained system state parameters are transmitted to the step size controller.
Preferably, the step length controller comprises a state selection module, and the state selection module selects the state of the system according to the system state parameters obtained by the single-frequency tone detector, and controls and adjusts the time-varying step length parameters
Figure 110427DEST_PATH_IMAGE011
Time-varying step size parameter
Figure 524091DEST_PATH_IMAGE011
To an adaptive filter.
For example, the step size controller corrects the coefficient according to the normalization factor
Figure 610996DEST_PATH_IMAGE012
And maximum single frequency energy obtained by the single frequency tone detector
Figure 84703DEST_PATH_IMAGE009
And the ratio of maximum single-frequency energy to total energy of power spectrum
Figure 257058DEST_PATH_IMAGE010
Judging the threshold value, and controlling and adjusting the time-varying step length parameter according to the judgment result
Figure 739992DEST_PATH_IMAGE011
The method specifically comprises the following steps:
1) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 681403DEST_PATH_IMAGE010
Less than a set threshold
Figure 591590DEST_PATH_IMAGE013
If yes, the system is judged to be in steady state convergence, and a preset steady state step length parameter is adopted
Figure 251242DEST_PATH_IMAGE014
As the time-varying step size parameter, in general,
Figure 475550DEST_PATH_IMAGE014
the value may be 0.05;
2) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 599364DEST_PATH_IMAGE010
Greater than a set threshold
Figure 618135DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 794776DEST_PATH_IMAGE009
Less than a set threshold
Figure 619513DEST_PATH_IMAGE015
If the system is determined to be in a related interference state, the normalization correction coefficient is used
Figure 535516DEST_PATH_IMAGE012
Correcting time-varying step length parameters:
Figure 787506DEST_PATH_IMAGE016
；
3) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 421750DEST_PATH_IMAGE010
Greater than a set threshold
Figure 784598DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 555108DEST_PATH_IMAGE009
Greater than a set threshold
Figure 977999DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 833959DEST_PATH_IMAGE012
Less than a set threshold
Figure 499DEST_PATH_IMAGE017
If yes, the system is judged to be in a squeaking state, at the moment, squeaking is preferentially processed, and a larger fixed step length parameter is adopted
Figure 891094DEST_PATH_IMAGE018
Filter iteration is accelerated:
Figure 484887DEST_PATH_IMAGE019
wherein
Figure 828143DEST_PATH_IMAGE020
；
4) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 532794DEST_PATH_IMAGE010
Greater than a set threshold
Figure 277896DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 544055DEST_PATH_IMAGE009
Greater than a set threshold
Figure 374607DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 882949DEST_PATH_IMAGE012
Greater than a set threshold
Figure 748137DEST_PATH_IMAGE017
If so, judging that the system is in a double-end sounding state, and setting the time-varying step length parameter to zero at the moment to stop the adaptive iteration of the filter:
Figure 683732DEST_PATH_IMAGE021
。
wherein the set threshold value
Figure 736002DEST_PATH_IMAGE013
、
Figure 48034DEST_PATH_IMAGE015
、
Figure 767729DEST_PATH_IMAGE017
Are all constants that can be derived from the particular system state adjustments.
Preferably, the adaptive filter includes a normalized error signal processing module, a coefficient updating module, and a FIR filter module, wherein:
the normalized error signal processing module is used for processing the error signal
Figure 874225DEST_PATH_IMAGE006
Far-end signal relative to loudspeaker
Figure 413791DEST_PATH_IMAGE004
Is normalized by the square of the Euclidean norm to obtain a normalized error signal
Figure 263935DEST_PATH_IMAGE022
；
Wherein,
Figure 838136DEST_PATH_IMAGE023
is the remote signal vector corresponding to the time delay, D is the adaptive filter order,
Figure 115533DEST_PATH_IMAGE025
is a very small constant and is used to prevent the denominator from being too small to cause divergence.
Normalizing error signals according to set frequency by convex combination first-order recursion process
Figure 407974DEST_PATH_IMAGE026
And performing snapshot smoothing to obtain a normalized average error.
The coefficient isThe new module obtains time-varying step length parameters according to the normalized error signal, the normalized average error and the step length controller
Figure 796230DEST_PATH_IMAGE011
And iteratively updating the adaptive filter coefficients.
The FIR filter module is used for far-end signal
Figure 490517DEST_PATH_IMAGE062
Filtering to obtain estimated echo signal
Figure 454929DEST_PATH_IMAGE005
And then outputting.
Correspondingly, the hearing aid adaptive echo cancellation device according to any one of the above items is suitable for a digital hearing aid system. The digital hearing aid automatically collects the conditions of the acoustic signal type, the signal-to-noise ratio, the strength difference of the front microphone and the rear microphone and the like of the environment where the digital hearing aid is located, defines different environments, and automatically adjusts the characteristics of noise reduction, direction, compression ratio and the like so as to adapt to the continuously changing environment. The phenomenon that a user of the analog machine cannot hear the sound with small sound and is difficult to hear with loud sound is avoided. Generally, a digital hearing aid system mainly includes an echo cancellation device, a microphone (or microphone), an amplifier, a receiver (or earphone), a battery, electro-acoustic devices such as various volume or tone control knobs, and a housing, wherein the echo cancellation device can adopt any one of the above-mentioned step-size-variable hearing aid adaptive echo cancellation devices.
Correspondingly, the adaptive echo cancellation method for the variable-step hearing aid comprises the following steps:
A. according to the cached far-end signal sample, the estimated echo signal is obtained through filtering of a self-adaptive FIR filter
Figure 969087DEST_PATH_IMAGE005
：
Figure 161034DEST_PATH_IMAGE028
Wherein
Figure 709827DEST_PATH_IMAGE029
，
Figure 329027DEST_PATH_IMAGE030
for the coefficients of the FIR filter,
Figure 330481DEST_PATH_IMAGE031
is composed of
Figure 326119DEST_PATH_IMAGE032
The conjugate transpose of (1); and the sampled near-end voice signal
Figure 729418DEST_PATH_IMAGE033
Subtracting the estimated echo signal
Figure 519520DEST_PATH_IMAGE005
To obtain an error signal
Figure 8270DEST_PATH_IMAGE034
。
B. Performing time-frequency transformation on the error signal, calculating a power spectrum of the error signal, analyzing energy distribution characteristics, and obtaining system state parameters, preferably, the step B specifically includes:
b1, continuously filling error signals into a buffer area of the single-frequency tone detector, performing one-time fast Fourier transform operation after the buffer area is full of data, resetting the buffer to obtain the frequency spectrum of the signals, and further calculating the power spectrum of the signals
Figure 807599DEST_PATH_IMAGE036
：
Figure 862143DEST_PATH_IMAGE037
Wherein
Figure 760828DEST_PATH_IMAGE038
as the number of frames,
Figure 799192DEST_PATH_IMAGE039
are the frequency points of the frequency,
Figure 74315DEST_PATH_IMAGE040
；
Figure 750409DEST_PATH_IMAGE041
is FFT operation;
Figure 85576DEST_PATH_IMAGE042
the number of fast Fourier transform points;
b2, finding the maximum energy frequency point according to the power spectrum of the signal
Figure 345656DEST_PATH_IMAGE044
Calculating the energy sum of the maximum energy frequency point and the adjacent frequency points
Figure 424470DEST_PATH_IMAGE009
：
Figure 453606DEST_PATH_IMAGE045
；
Calculating the ratio of the maximum single-frequency energy to the total energy of the power spectrum
Figure 959674DEST_PATH_IMAGE010
：
Figure 707050DEST_PATH_IMAGE046
；
Wherein,
Figure 323976DEST_PATH_IMAGE042
the number of fast Fourier transform points;
the state parameter is measured
Figure 473198DEST_PATH_IMAGE009
、
Figure 150167DEST_PATH_IMAGE010
To the step size controller.
C、Judging the state of the system according to the system state parameters, and controlling the self-adaptive time-varying step length parameters
Figure 384839DEST_PATH_IMAGE011
. Preferably, the step C specifically includes:
c1 maximum ratio of single-frequency energy to total energy of power spectrum obtained by single-frequency tone detector
Figure 805456DEST_PATH_IMAGE010
Smooth normalization correction coefficient
Figure 809184DEST_PATH_IMAGE012
：
Figure 657054DEST_PATH_IMAGE047
；
Wherein,
Figure 379023DEST_PATH_IMAGE048
a forgetting factor, a positive number less than 1;
Figure 337751DEST_PATH_IMAGE049
，
Figure 960100DEST_PATH_IMAGE050
for controlling correction coefficient
Figure 713293DEST_PATH_IMAGE012
Between 0 and 1;
Figure 922557DEST_PATH_IMAGE051
for the set threshold, the value is generally 0.5.
C2 maximum single frequency energy
Figure 684977DEST_PATH_IMAGE009
Ratio of maximum single-frequency energy to total energy of power spectrum
Figure 663297DEST_PATH_IMAGE052
Normalized correction factor
Figure 852970DEST_PATH_IMAGE012
Performing threshold judgment, and adjusting the time-varying step length parameter according to the judgment results of the three state parameters, wherein the preferable step C2 specifically comprises:
1) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 283951DEST_PATH_IMAGE010
Less than a set threshold
Figure 584483DEST_PATH_IMAGE013
If yes, the system is judged to be in steady state convergence, and a preset steady state step length parameter is adopted
Figure 682889DEST_PATH_IMAGE014
As a time-varying step size parameter;
2) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 43463DEST_PATH_IMAGE010
Greater than a set threshold
Figure 961740DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 862700DEST_PATH_IMAGE009
Less than a set threshold
Figure 753296DEST_PATH_IMAGE015
If the system is determined to be in a related interference state, the normalization correction coefficient is used
Figure 347088DEST_PATH_IMAGE012
Correcting time-varying step length parameters:
Figure 690345DEST_PATH_IMAGE016
；
3) if the maximum single frequency energy occupies powerRatio of total energy of spectrum
Figure 896461DEST_PATH_IMAGE010
Greater than a set threshold
Figure 641563DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 406256DEST_PATH_IMAGE009
Greater than a set threshold
Figure 236809DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 745151DEST_PATH_IMAGE012
Less than a set threshold
Figure 344759DEST_PATH_IMAGE017
If yes, the system is judged to be in a howling state, and at the moment, howling is preferentially processed, and a fixed step length parameter is adopted
Figure 280354DEST_PATH_IMAGE018
Filter iteration is accelerated:
Figure 598203DEST_PATH_IMAGE019
wherein
Figure 910236DEST_PATH_IMAGE020
；
4) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 364351DEST_PATH_IMAGE010
Greater than a set threshold
Figure 470847DEST_PATH_IMAGE013
And maximum single frequency energy
Figure 275992DEST_PATH_IMAGE009
Greater than a set threshold
Figure 126137DEST_PATH_IMAGE015
And normalized correction coefficient
Figure 700337DEST_PATH_IMAGE012
Greater than a set threshold
Figure 977735DEST_PATH_IMAGE017
If so, judging that the system is in a double-end sounding state, and setting the time-varying step length parameter to zero at the moment to stop the adaptive iteration of the filter:
Figure 270176DEST_PATH_IMAGE021
。
D. for error signal
Figure 162827DEST_PATH_IMAGE006
Far-end signal relative to loudspeaker
Figure 591534DEST_PATH_IMAGE004
The square of the Euclidean norm is normalized to obtain a normalized error mean value
Figure 305412DEST_PATH_IMAGE008
And smoothing the maximum value of each frame of the normalized error signal by using a convex combination first-order recursion process to be used as an upper limit threshold value of the normalized adaptive error.
Preferably, the step D specifically includes:
d1, for the current error signal
Figure 819570DEST_PATH_IMAGE006
Far-end signal relative to loudspeaker
Figure 11517DEST_PATH_IMAGE004
Square of the euclidean norm of
Figure 560310DEST_PATH_IMAGE053
Normalization is performed to obtain a normalized error signal
Figure 179510DEST_PATH_IMAGE026
：
Figure 180964DEST_PATH_IMAGE022
；
Wherein,
Figure 176602DEST_PATH_IMAGE025
is a very small constant and is used to prevent the denominator from being too small to cause divergence.
D2, calculating the absolute value of the normalized error signal of each frame
Figure 579901DEST_PATH_IMAGE054
Maximum value of
Figure 370003DEST_PATH_IMAGE055
And smoothing the data by convex combination first order recursion process to obtain normalized error mean of normalized error signal
Figure 858753DEST_PATH_IMAGE008
：
Figure 392503DEST_PATH_IMAGE056
；
Wherein,
Figure 650309DEST_PATH_IMAGE057
and
Figure 876891DEST_PATH_IMAGE058
in order to be a forgetting factor,
Figure 852937DEST_PATH_IMAGE057
the value is generally small: preferably, the first and second liquid crystal materials are,
Figure 426263DEST_PATH_IMAGE063
，
Figure 804155DEST_PATH_IMAGE058
large value, preferably
Figure 936059DEST_PATH_IMAGE064
；
D3, normalizing the normalized error mean of the error signal
Figure 399401DEST_PATH_IMAGE008
As the upper limit of the threshold value of the error signal, the sudden change of the error signal caused by the interference situation such as double-end sounding is prevented:
Figure 274953DEST_PATH_IMAGE065
E. using modified time-varying step-size parameters
Figure 304089DEST_PATH_IMAGE011
And the normalized error iteratively updates the FIR filter coefficient:
Figure 810157DEST_PATH_IMAGE035
。
the present invention and the prior art are implemented below in conjunction with the HA320D digital hearing aid chip of Nanjing Tianyue electronics, Inc., where the HA320D digital hearing aid system sample rate is 16kHZ, and the quantization bit number is 16 bits;
Figure 291954DEST_PATH_IMAGE066
，
Figure 971197DEST_PATH_IMAGE067
，
Figure 58101DEST_PATH_IMAGE068
，
Figure 797387DEST_PATH_IMAGE015
needs to be measured according to the quantification of the system and various parameter conditions in the howling critical state
Figure 969743DEST_PATH_IMAGE009
Obtaining;
Figure 187097DEST_PATH_IMAGE014
the value of the carbon dioxide is 0.05,
Figure 394088DEST_PATH_IMAGE018
the value is 0.1;
Figure 802810DEST_PATH_IMAGE057
the value of the additive is 0.001,
Figure 462462DEST_PATH_IMAGE058
the value is 0.5;
Figure 483507DEST_PATH_IMAGE025
the value is 0.001.
As shown in fig. 2, in a real hearing aid closed-loop environment, the adaptive echo cancellation device and the echo cancellation method for a hearing aid in variable step sizes of the present invention have the following significant advantages:
1) the anti-interference capability under the external noise or double-end talkback scene is strong, and the iterative divergence of the adaptive filter can be obviously prevented;
2) imbalance can be effectively prevented when the device is in an environment with strong noise single-frequency energy;
3) the convergence speed and the steady-state error of the adaptive filter are well balanced, and a time-varying system and howling suppression can be quickly tracked;
4) by means of the multiplying unit, FFT and other modules of the hearing aid chip, the algorithm is low in complexity and power consumption.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A step size-variable hearing aid adaptive echo cancellation device is characterized by comprising a single-frequency tone detector, a step size controller and an adaptive filter:
the single tone detector is used for correcting error signals
Figure 945414DEST_PATH_IMAGE002
Carrying out spectrum energy analysis on the sample, calculating the current state parameter of the hearing aid system, and transmitting the parameter to the step length controller;
the step size controller is used for obtaining a normalized error mean value according to the system state parameters obtained from the single-frequency tone detector
Figure 349851DEST_PATH_IMAGE003
Judging the state of the system, and calculating the time-varying step length parameter of the adaptive filter
Figure 198858DEST_PATH_IMAGE004
And passes it to the adaptive filter;
the adaptive filter is used for buffering loudspeaker far-end signals
Figure 979732DEST_PATH_IMAGE005
Filtering the samples to calculate an estimated echo signal
Figure 230585DEST_PATH_IMAGE006
Then outputting, and carrying out iterative updating on the self-adaptive filter according to the time-varying step length parameter calculated by the step length controller;
wherein the error signal
Figure 805923DEST_PATH_IMAGE002
For near-end speech signals
Figure 142226DEST_PATH_IMAGE007
Subtracting the estimated echo signal
Figure 461212DEST_PATH_IMAGE008
；
Normalized mean of error
Figure 566571DEST_PATH_IMAGE003
Is an error signal
Figure 312810DEST_PATH_IMAGE002
Relative to the far-end signal
Figure 870831DEST_PATH_IMAGE005
Normalized long term average.
2. The variable step size hearing aid adaptive echo cancellation device according to claim 1, wherein the single frequency tone detector comprises a frame FFT module and a spectral energy analysis module:
the frame FFT module is used for receiving the buffered error signal
Figure 993507DEST_PATH_IMAGE002
For the error signal
Figure 953373DEST_PATH_IMAGE002
Performing fast Fourier transform according to a set frequency, calculating a power spectrum of the signal and transmitting the power spectrum to a spectrum energy analysis module;
the spectrum energy analysis module analyzes the maximum single-frequency energy of the obtained signal spectrum
Figure 363189DEST_PATH_IMAGE009
Ratio of maximum single-frequency energy to total energy of power spectrum
Figure 674085DEST_PATH_IMAGE010
And the obtained system state parameters are transmitted to the step size controller.
3. The apparatus of claim 1, wherein the step size controller comprises a state selection module, and the state selection module obtains the state according to a single tone detectorSelecting the state of the system by the system state parameters, and controlling and adjusting the time-varying step length parameters
Figure 334873DEST_PATH_IMAGE004
Time-varying step size parameter
Figure 149246DEST_PATH_IMAGE004
To an adaptive filter.
4. The adaptive echo cancellation device of claim 3, wherein the step size controller is configured to modify the echo cancellation signal according to a normalization correction factor
Figure 502867DEST_PATH_IMAGE011
And maximum single frequency energy obtained by the single frequency tone detector
Figure 35479DEST_PATH_IMAGE009
And the ratio of maximum single-frequency energy to total energy of power spectrum
Figure 234379DEST_PATH_IMAGE010
Judging the threshold value, and controlling and adjusting the time-varying step length parameter according to the judgment result
Figure 168837DEST_PATH_IMAGE004
The method specifically comprises the following steps:
1) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 693359DEST_PATH_IMAGE010
Less than a set threshold
Figure 447689DEST_PATH_IMAGE012
If yes, the system is judged to be in steady state convergence, and a preset steady state step length parameter is adopted
Figure 715859DEST_PATH_IMAGE013
As a time-varying step size parameter;
2) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 504824DEST_PATH_IMAGE010
Greater than a set threshold
Figure 934668DEST_PATH_IMAGE012
And maximum single frequency energy
Figure 441873DEST_PATH_IMAGE009
Less than a set threshold
Figure 248155DEST_PATH_IMAGE014
If the system is determined to be in a related interference state, the normalization correction coefficient is used
Figure 891626DEST_PATH_IMAGE011
Correcting time-varying step length parameters:
Figure 259415DEST_PATH_IMAGE015
；
3) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 988337DEST_PATH_IMAGE010
Greater than a set threshold
Figure 598310DEST_PATH_IMAGE012
And maximum single frequency energy
Figure 361866DEST_PATH_IMAGE009
Greater than a set threshold
Figure 399093DEST_PATH_IMAGE014
And normalized correction coefficient
Figure 880889DEST_PATH_IMAGE011
Less than a set threshold
Figure 28974DEST_PATH_IMAGE016
If yes, the system is judged to be in a howling state, and at the moment, howling is preferentially processed, and a fixed step length parameter is adopted
Figure 647037DEST_PATH_IMAGE017
Filter iteration is accelerated:
Figure 589585DEST_PATH_IMAGE018
wherein
Figure 293099DEST_PATH_IMAGE019
；
4) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 244875DEST_PATH_IMAGE010
Greater than a set threshold
Figure 717444DEST_PATH_IMAGE012
And maximum single frequency energy
Figure 96473DEST_PATH_IMAGE009
Greater than a set threshold
Figure 287283DEST_PATH_IMAGE014
And normalized correction coefficient
Figure 777170DEST_PATH_IMAGE011
Greater than a set threshold
Figure 868361DEST_PATH_IMAGE016
If so, judging that the system is in a double-end sounding state, and setting the time-varying step length parameter to zero at the moment to stop the adaptive iteration of the filter:
Figure 418291DEST_PATH_IMAGE020
。
5. the variable step size hearing aid adaptive echo cancellation device according to claim 1, wherein the adaptive filter comprises a normalized error signal processing module, a coefficient update module, and a FIR filter module:
the normalized error signal processing module is used for processing the error signal
Figure 830818DEST_PATH_IMAGE002
Far-end signal relative to loudspeaker
Figure 124396DEST_PATH_IMAGE005
Is normalized by the square of the Euclidean norm to obtain a normalized error signal
Figure 571557DEST_PATH_IMAGE021
；
Wherein,
Figure 292389DEST_PATH_IMAGE022
is the far-end signal vector for the corresponding time delay,
Figure 457791DEST_PATH_IMAGE023
in order to adapt the order of the filter,
Figure 289481DEST_PATH_IMAGE024
is a constant;
normalizing error signals according to set frequency by convex combination first-order recursion process
Figure 591149DEST_PATH_IMAGE025
Performing snapshot smoothing to obtain a normalized average error;
the coefficient updating module obtains time-varying step length parameters according to the normalized error signals, the normalized average errors and the step length controller
Figure 482882DEST_PATH_IMAGE004
Iteratively updating the adaptive filter coefficients;
the FIR filter module is used for far-end signal
Figure 870001DEST_PATH_IMAGE026
Filtering to obtain estimated echo signal
Figure 505381DEST_PATH_IMAGE008
And then outputting.
6. The variable-stride hearing-aid adaptive echo cancellation device of any one of claims 1-5, wherein the variable-stride hearing-aid adaptive echo cancellation device is adapted for use in a digital hearing-aid system.
7. A method for adaptive echo cancellation in a variable step size hearing aid, comprising the steps of:
A. according to the cached far-end signal sample, the estimated echo signal is obtained through filtering of a self-adaptive FIR filter
Figure 927135DEST_PATH_IMAGE006
：
Figure 989769DEST_PATH_IMAGE027
Wherein
Figure 864184DEST_PATH_IMAGE028
，
Figure 37677DEST_PATH_IMAGE029
for the coefficients of the FIR filter,
Figure 815402DEST_PATH_IMAGE030
is composed of
Figure 580096DEST_PATH_IMAGE031
The conjugate transpose of (1); and the sampled near-end voice signal
Figure 941807DEST_PATH_IMAGE007
Subtracting the estimated echo signal
Figure 918990DEST_PATH_IMAGE006
To obtain an error signal
Figure 315337DEST_PATH_IMAGE032
；
B. Performing time-frequency transformation on the error signal, calculating the power spectrum of the error signal and analyzing the energy distribution characteristic to obtain system state parameters;
C. judging the state of the system according to the system state parameters, and controlling the self-adaptive time-varying step length parameters
Figure 719773DEST_PATH_IMAGE004
；
D. For error signal
Figure 303201DEST_PATH_IMAGE002
Far-end signal relative to loudspeaker
Figure 84075DEST_PATH_IMAGE005
The square of the Euclidean norm is normalized to obtain a normalized error mean value
Figure 334928DEST_PATH_IMAGE003
Carrying out smooth processing on the maximum value of each frame of the normalized error signal by using a convex combination first-order recursion process, and using the maximum value as an upper limit threshold value of the normalized adaptive error;
E. using modified time-varying step-size parameters
Figure 175845DEST_PATH_IMAGE004
And the normalized error iteratively updates the FIR filter coefficient:
Figure 246569DEST_PATH_IMAGE033
。
8. the method according to claim 7, wherein the step B specifically comprises:
b1, continuously filling error signals into a buffer area of the single-frequency tone detector, performing one-time fast Fourier transform operation after the buffer area is full of data, resetting the buffer to obtain the frequency spectrum of the signals, and further calculating the power spectrum of the signals
Figure 565555DEST_PATH_IMAGE034
：
Figure 670915DEST_PATH_IMAGE035
Wherein
Figure 921548DEST_PATH_IMAGE036
as the number of frames,
Figure 745148DEST_PATH_IMAGE037
are the frequency points of the frequency,
Figure 602245DEST_PATH_IMAGE038
；
Figure 827690DEST_PATH_IMAGE039
is FFT operation;
Figure 744831DEST_PATH_IMAGE040
the number of fast Fourier transform points;
b2, finding the maximum energy frequency point according to the power spectrum of the signal
Figure 790147DEST_PATH_IMAGE041
Calculating the energy sum of the maximum energy frequency point and the adjacent frequency points
Figure 450936DEST_PATH_IMAGE009
：
Figure 530887DEST_PATH_IMAGE042
；
Calculating the ratio of the maximum single-frequency energy to the total energy of the power spectrum
Figure 618929DEST_PATH_IMAGE010
：
Figure 151541DEST_PATH_IMAGE043
；
Wherein,
Figure 616021DEST_PATH_IMAGE040
the number of fast Fourier transform points;
the state parameter is measured
Figure 550479DEST_PATH_IMAGE009
、
Figure 809422DEST_PATH_IMAGE010
To the step size controller.
9. The method according to claim 7, wherein the step C specifically comprises:
c1 maximum ratio of single-frequency energy to total energy of power spectrum obtained by single-frequency tone detector
Figure 829330DEST_PATH_IMAGE010
Smooth normalization correction coefficient
Figure 97501DEST_PATH_IMAGE011
：
Figure 886465DEST_PATH_IMAGE044
；
Wherein,
Figure 817774DEST_PATH_IMAGE045
a forgetting factor, a positive number less than 1;
Figure 324979DEST_PATH_IMAGE047
，
Figure 131261DEST_PATH_IMAGE048
for controlling correction coefficient
Figure 774732DEST_PATH_IMAGE011
Between 0 and 1;
Figure 641057DEST_PATH_IMAGE049
is a set threshold value;
c2 maximum single frequency energy
Figure 635557DEST_PATH_IMAGE009
Ratio of maximum single-frequency energy to total energy of power spectrum
Figure 245530DEST_PATH_IMAGE050
Normalized correction factor
Figure 743508DEST_PATH_IMAGE011
And judging a threshold value, and adjusting a time-varying step length parameter according to the judgment results of the three state parameters, specifically:
1) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 780734DEST_PATH_IMAGE010
Less than a set threshold
Figure 996952DEST_PATH_IMAGE012
If the system is determined to be stableState convergence by using a preset steady-state step length parameter
Figure 145036DEST_PATH_IMAGE013
As a time-varying step size parameter;
2) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 763099DEST_PATH_IMAGE010
Greater than a set threshold
Figure 971227DEST_PATH_IMAGE012
And maximum single frequency energy
Figure 674741DEST_PATH_IMAGE009
Less than a set threshold
Figure 626516DEST_PATH_IMAGE014
If the system is determined to be in a related interference state, the normalization correction coefficient is used
Figure 597621DEST_PATH_IMAGE011
Correcting time-varying step length parameters:
Figure 976650DEST_PATH_IMAGE015
；
3) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 167460DEST_PATH_IMAGE010
Greater than a set threshold
Figure 657347DEST_PATH_IMAGE012
And maximum single frequency energy
Figure 250002DEST_PATH_IMAGE009
Greater than a set threshold
Figure 534353DEST_PATH_IMAGE014
And normalized correction coefficient
Figure 212459DEST_PATH_IMAGE011
Less than a set threshold
Figure 506037DEST_PATH_IMAGE016
If yes, the system is judged to be in a howling state, and at the moment, howling is preferentially processed, and a fixed step length parameter is adopted
Figure 953199DEST_PATH_IMAGE017
Filter iteration is accelerated:
Figure 674030DEST_PATH_IMAGE018
wherein
Figure 573853DEST_PATH_IMAGE019
；
4) if the maximum single-frequency energy accounts for the total energy ratio of the power spectrum
Figure 405543DEST_PATH_IMAGE010
Greater than a set threshold
Figure 972790DEST_PATH_IMAGE012
And maximum single frequency energy
Figure 864523DEST_PATH_IMAGE009
Greater than a set threshold
Figure 251642DEST_PATH_IMAGE014
And normalized correction coefficient
Figure 887023DEST_PATH_IMAGE011
Greater than a set threshold
Figure 810242DEST_PATH_IMAGE016
If so, judging the system to be in a double-end sounding state, and determining the time-varying step length parameter at the momentZero-stopping the adaptive iteration of the filter:
Figure 872876DEST_PATH_IMAGE020
。
10. the method according to claim 7, wherein the step D specifically comprises:
d1, for the current error signal
Figure 747291DEST_PATH_IMAGE002
Far-end signal relative to loudspeaker
Figure 920783DEST_PATH_IMAGE005
Square of the euclidean norm of
Figure 197044DEST_PATH_IMAGE051
Normalization is performed to obtain a normalized error signal
Figure 430579DEST_PATH_IMAGE025
：
Figure 792290DEST_PATH_IMAGE021
；
Wherein,
Figure 769473DEST_PATH_IMAGE024
is a constant;
d2, calculating the absolute value of the normalized error signal of each frame
Figure 900240DEST_PATH_IMAGE052
Maximum value of
Figure 304677DEST_PATH_IMAGE053
And smoothing the data by convex combination first order recursion process to obtain normalized error mean of normalized error signal
Figure 153684DEST_PATH_IMAGE003
：
Figure 200138DEST_PATH_IMAGE054
；
Wherein,
Figure 185411DEST_PATH_IMAGE055
and
Figure 760749DEST_PATH_IMAGE056
is a forgetting factor;
d3, normalizing the normalized error mean of the error signal
Figure 831473DEST_PATH_IMAGE003
As the upper threshold limit for the error signal.
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