CN107564539B - Acoustic echo cancellation method and device facing microphone array - Google Patents

Acoustic echo cancellation method and device facing microphone array Download PDF

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CN107564539B
CN107564539B CN201710757604.4A CN201710757604A CN107564539B CN 107564539 B CN107564539 B CN 107564539B CN 201710757604 A CN201710757604 A CN 201710757604A CN 107564539 B CN107564539 B CN 107564539B
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echo cancellation
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官威
张李
吴科苇
李志�
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Suzhou Qdreamer Network Technology Co ltd
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Abstract

The invention relates to a microphone array-oriented acoustic echo cancellation method, which comprises the steps that a microphone array collects data of near-end signals and echo signals in real time, channel signals of one microphone are selected, an initialization model is built according to a self-adaptive filtering thought and an independent component analysis algorithm, an echo cancellation model is built according to the initialization model to perform echo cancellation on single-channel signals of the microphone, and echo cancellation estimation models of other microphones in the microphone array are built according to the initial echo cancellation model and the filter coefficients of single channels to perform echo cancellation; the device provided by the invention performs echo cancellation on the multi-channel recording signal and the echo signal of the measuring system by arranging the acoustic sensor at the key position on the annular sensor array, so as to obtain the echo cancellation signal of the microphone array, and finally achieve the purpose of improving the voice recognition rate.

Description

Acoustic echo cancellation method and device facing microphone array
Technical Field
The invention relates to the field of digital signal processing, in particular to an acoustic echo cancellation method and device for a microphone array.
Background
With the advent of the artificial intelligence era, the voice technology has received more and more attention as an interface for human-computer interaction. The traditional near-field voice interaction technology cannot meet the requirements of people, and people hope to develop intelligent equipment capable of controlling voice in more distant and complex scenes. Thus, microphone array technology becomes the core of far-field speech interaction.
By microphone array is meant a system of a plurality of microphones in which a certain number of acoustic sensors (microphones) are arranged in a certain regular pattern and applied to the processing of speech signals. In the traditional voice interaction application scene, a single microphone is mainly adopted, but a single microphone system can obtain a signal meeting the voice recognition requirement only under the near conditions of close sound source, low noise and no reverberation, so that the single microphone system has certain limitation. For the application scenario of far-field speech recognition, the quality of signals picked up by a microphone system is poor due to a large amount of noise, reverberation and echo contained in the real environment, and the recognition rate of speech is seriously affected. And due to the problems of multiple sound sources and environmental noise, the single-microphone system is difficult to separate and locate the sound sources, so the multi-microphone system is required to assist the front-end signal processing of speech recognition.
Aiming at the current complex application scene, a series of key technologies capable of effectively improving the speech recognition rate are developed based on a microphone array, and the key technologies mainly comprise: speech enhancement, sound source localization, reverberation cancellation, echo cancellation, noise suppression. The voice enhancement technology mainly adopts a beam forming method, which mainly enhances sound in a specific direction and inhibits sound interference except a main lobe; sound source positioning, which mainly refers to calculating the angle and distance of a target speaker by using a microphone array so as to realize the tracking of the target speaker and the directional pickup of sound; reverberation elimination, which mainly utilizes signal preprocessing means such as inverse filtering or linear prediction to eliminate the phenomenon of mutual superposition of asynchronous voices influencing voice recognition; echo cancellation, which mainly utilizes means such as adaptive signal processing to eliminate phenomena such as accent in interference speech recognition; and noise suppression, wherein noise reduction methods such as spectral subtraction are mainly used for eliminating the situation of large background noise in a speech recognition application scene.
Based on the engineering application background, echo cancellation is taken as one of key technologies of a microphone array, and important technical support can be provided for far-field voice interaction for a multi-channel acoustic echo cancellation algorithm under the microphone array.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a microphone array-oriented acoustic echo cancellation method and device based on the combination of an independent component analysis algorithm and a self-adaptive filtering idea, aiming at the problem that acoustic echo cancellation is difficult in far-field speech recognition.
According to the acoustic echo cancellation method facing the microphone array, the microphone array collects data of near-end signals and echo signals in real time;
selecting a microphone channel signal output by one of the microphones, constructing an initialization model according to a self-adaptive filtering thought and an independent component analysis algorithm, and establishing an echo cancellation model according to the initialization model to perform echo cancellation on the microphone channel signal;
and constructing echo cancellation estimation models of other microphones in the microphone array according to the initial echo cancellation model and the single-channel filter coefficient for echo cancellation.
Further, the microphone channel signal includes a near-end signal and an echo signal collected by the microphone.
Further, the initialization model includes a functional relationship between the echo signal and the far-end signal in the microphone channel signal and a functional relationship between the echo signal and the far-end signal estimated in the other microphone channel signals as
Figure BDA0001392534160000021
And
Figure BDA0001392534160000022
wherein
Figure BDA0001392534160000023
An impulse response of a far-end signal propagating through space,
Figure BDA0001392534160000024
in order to be an echo signal, the echo signal,
Figure BDA0001392534160000025
in order to estimate the echo signal, it is,
Figure BDA0001392534160000026
in order to be a far-end signal,
Figure BDA0001392534160000027
is the estimated adaptive filter coefficients.
Further, the relationship between the estimated echo signal and the error signal for controlling the convergence of the adaptive filter is
Figure BDA0001392534160000028
Wherein
Figure BDA0001392534160000029
Is the microphone channel signal.
Further, the echo cancellation model is
Figure BDA0001392534160000031
Wherein
Figure BDA0001392534160000032
Is the near-end signal.
Further, the echo cancellation estimation model is
Figure BDA0001392534160000033
Wherein
Figure BDA0001392534160000034
Is a non-0 scalar.
More particularly, the
Figure BDA0001392534160000035
The solution was performed by Fast ICA.
The invention provides an acoustic echo cancellation device facing a microphone array, which comprises a central processing module, an acquisition module, a storage module, a power supply module, an upper computer communication module, a reset module and a key control module, wherein the central processing module is used for controlling the acquisition module and processing signals acquired by the acquisition module, the storage module is used for storing signals input by a central processing unit into the storage module and signals output by the storage module to the central processing module, the upper computer communication module is used for processing the signals processed by the central processing module and controlling the central processing module, the reset module is used for controlling the reset of the central processing module, and the key control module is used for inputting parameters into the central processing module. The acoustic echo cancellation method and device for the microphone array can achieve echo cancellation under multiple channels, and improve voice recognition rate.
Furthermore, the central processing unit module is an OMAP dual-core processor based on an ARM core and a DSP core.
Further, the acquisition module is a microphone array data acquisition module.
Further, the upper computer communication module further comprises a cloud server for voice recognition.
The acoustic echo cancellation method and device for the microphone array can effectively perform multi-channel echo cancellation on a multi-microphone array system, provide effective preprocessing algorithm technical support for rear-end speech recognition, and are applied to devices or systems such as intelligent robots, intelligent sound boxes and intelligent conferences.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
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Fig. 1 is a functional block diagram of an algorithm of an acoustic echo cancellation method for a microphone array according to the present invention;
fig. 2 is a block diagram of an acoustic echo cancellation device facing a microphone array according to the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 shows a preferred embodiment of an acoustic echo cancellation method facing a microphone array according to the present invention. In this embodiment:
firstly, a microphone array collects data of a near-end signal in a recording channel and an echo signal in an echo channel in real time, then a microphone channel signal output by one of the microphones is selected, an initialization model of an ICA (independent component analysis) is built according to the data in the microphone channel signal and an adaptive filtering thought and an independent component analysis algorithm, an echo cancellation model is built according to the initialization model of the ICA to perform echo cancellation on the microphone channel signal, and an echo cancellation estimation model of other microphones in the microphone array is built according to the initial echo cancellation model and a filter coefficient of a single channel to perform echo cancellation.
Preferably, the method comprises the following specific steps:
s1, setting the measured far-end signal as
Figure BDA0001392534160000041
Signal D collected by microphone arraykIs composed of
Figure BDA0001392534160000042
Wherein m represents the number of acoustic sensors arranged on the microphone structure, k represents the number of time domain sampling points, and j is more than or equal to 1 and less than or equal to m; i is more than or equal to 1 and less than or equal to k;
s2, setting the near-end voice signal as
Figure BDA0001392534160000043
The echo signal is
Figure BDA0001392534160000044
Therefore, the j-th microphone channel signal, the near-end signal and the echo signal satisfy the following relations:
Figure BDA0001392534160000045
s3, setting the impulse response of the far-end signal through space propagation as
Figure BDA0001392534160000046
Echo signal
Figure BDA0001392534160000047
And remote end signal
Figure BDA0001392534160000048
The relationship of (1) is:
Figure BDA0001392534160000049
s4, setting the estimated echo signal as
Figure BDA00013925341600000410
The estimated adaptive filter coefficient is
Figure BDA00013925341600000411
Error signal for estimating relation between echo signal and far-end signal and controlling adaptive filtering convergence
Figure BDA00013925341600000412
The relationship is as follows:
Figure BDA0001392534160000051
Figure BDA0001392534160000052
s5, constructing an acoustic echo cancellation ICA model based on the ICA idea, wherein the model equation can be expressed as:
Figure BDA0001392534160000053
wherein the content of the first and second substances,
Figure BDA0001392534160000054
in order to obtain the desired original signal,
Figure BDA0001392534160000055
in order to observe the vector, the vector is,
Figure BDA0001392534160000056
is a mixing matrix;
s6, an equation for separating the original signals can be established according to S05, which can be expressed as follows:
Figure BDA0001392534160000057
wherein the content of the first and second substances,
Figure BDA0001392534160000058
is a non-0 scalar to obtain
Figure BDA0001392534160000059
S7, in order to separate the target voice as much as possible, Fast ICA method is adopted to solve
Figure BDA00013925341600000510
The method comprises the following specific steps:
(a) to observation data matrix
Figure BDA00013925341600000511
Carrying out equalization;
(b) is provided with
Figure BDA00013925341600000512
Whitening observation data matrix x (Z ═ vx), where v ═ D-1/2ETD, E are feature values and feature vectors corresponding to the covariance matrix of the observation data matrix x respectively;
(c) selecting the number of components to be separated of ICA, and setting a counter l to be 1;
(d) setting initial random weight coefficients
Figure BDA00013925341600000513
(e) Update solving
Figure BDA00013925341600000514
(f) Decorrelation:
Figure BDA00013925341600000515
(g) normalization weight coefficient:
Figure BDA00013925341600000516
(h) if it is not
Figure BDA00013925341600000517
Non-convergence
Figure BDA00013925341600000518
Returning to the step (e);
(i) iteration l ═ l +1, if l ≦ m, return to step (d);
s8, for the j +1 th channel, the weight coefficient obtained by S07
Figure BDA0001392534160000061
And approximating echo cancellation of other channels, wherein the equation is as follows:
Figure BDA0001392534160000062
the estimated calculation formula for the near-end signals in the other microphone channel signals is as follows:
Figure BDA0001392534160000063
thus, the method utilizes Independent Component Analysis (ICA) algorithm and adaptive filtering idea to construct an echo cancellation estimation model, separates target voice, namely near-end signal, from far-end signal and microphone pick-up signal, and finally transmits the separated target voice to a recognition end, thereby achieving the purposes of echo cancellation and voice recognition.
Referring to fig. 2, fig. 2 is a preferred embodiment of an acoustic echo cancellation device facing a microphone array according to the present invention, for implementing the above-mentioned acoustic echo cancellation method facing the microphone array. In this embodiment:
the acoustic echo cancellation device facing the microphone array comprises a central processing module, an acquisition module, a storage module, a power supply module, an upper computer communication module, a reset module and a keying module, wherein the central processing module is used for controlling the acquisition module and processing signals acquired by the acquisition module, the storage module is used for storing signals input into the storage module by a central processing unit and signals output to the central processing module by the storage module, the upper computer communication module is used for processing signals processed by the central processing module and controlling the central processing module, the reset module is used for controlling the reset of the central processing module, and the keying module is used for inputting parameters into the central processing module.
Preferably, in order to make the central processing module have low power consumption and strong data processing capability, the central processing module is an OMAP dual-core processor having a dual-core ARM core and a DSP core structure.
Preferably, the acquisition module is a microphone array data acquisition module having functions of signal input, signal conditioning, and a/D data acquisition and conversion.
As preferred, host computer communication module still includes the high in the clouds server that is used for carrying out speech recognition, like this, host computer communication module can carry out speech recognition with the data after the echo cancellation's discernment end on the high in the clouds server of network transmission.
The working steps of the acoustic echo cancellation device facing the microphone array are as follows:
firstly, parameter setting is carried out on the working state, channel control, signal type acquisition, sampling frequency and the like of the device through an upper computer communication module or a keying module, a parameter instruction is transmitted to a central processing module, and a driving acquisition module acquires voice data; then, the DSP module of the OMAP processor performs echo cancellation on the echo channel signals acquired by the microphone array and the mixed signals acquired by the recording channel; and finally, transmitting the data after echo cancellation to a voice recognition system of a cloud server of the upper computer communication module through a network.
The acoustic echo cancellation device facing the microphone array arranges a plurality of acoustic sensors on key points of a ring-shaped microphone array structure, performs echo cancellation on a voice signal obtained by measurement in real time, performs echo cancellation on a system, and applies the acoustic echo cancellation device to an intelligent sound box or an intelligent robot. The multichannel echo cancellation device takes an OMAP embedded processor as a core and integrates units for data acquisition, data storage, control, data processing and the like, the device is designed to fully utilize dual-core ARM core and DSP core structures of the OMAP, and has the functions of low ARM core power consumption, high processing speed, flexible task scheduling and the like and the function of powerful digital processing analysis of the DSP core, and the two are effectively combined to realize real-time online acquisition, processing, transmission and analysis of voice signals. Meanwhile, the Ethernet is adopted for data transmission, so that the data is transmitted quickly and efficiently, the loss of signals in transmission is avoided, resource sharing is realized, and the defects of offline and delay of traditional data acquisition are overcome.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, it should be noted that, for those skilled in the art, many modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (4)

1. An acoustic echo cancellation method facing a microphone array is characterized in that:
the microphone array collects near-end signals and echo signal data in real time;
selecting a microphone channel signal acquired by one microphone, constructing an initialization model according to a self-adaptive filtering thought and an independent component analysis algorithm, and establishing an echo cancellation model according to the initialization model to perform echo cancellation on the microphone channel signal; according to the initial echo cancellation model and the filter coefficient of the single channel, constructing echo cancellation estimation models of other microphones in the microphone array for echo cancellation;
the microphone channel comprises a near-end signal and an echo signal collected by the microphone;
the method specifically comprises the following steps: s1, setting the measured far-end signal as
Figure FDA0003275640000000011
Signal D collected by microphone arraykComprises the following steps:
Figure FDA0003275640000000012
wherein m represents the number of acoustic sensors arranged on the microphone structure, k represents the number of time domain sampling points, and j is more than or equal to 1 and less than or equal to m; i is more than or equal to 1 and less than or equal to k;
s2, setting the near-end voice signal as
Figure FDA0003275640000000013
The echo signal is
Figure FDA0003275640000000014
Therefore, the j-th microphone channel signal, the near-end signal and the echo signal satisfy the following relations:
Figure FDA0003275640000000015
s3, setting the impulse response of the far-end signal through space propagation as
Figure FDA0003275640000000016
Echo signal
Figure FDA0003275640000000017
And remote end signal
Figure FDA0003275640000000018
The relationship of (1) is:
Figure FDA0003275640000000019
s4, setting the estimated echo signal as
Figure FDA00032756400000000110
The estimated adaptive filter coefficient is
Figure FDA00032756400000000111
Error signal for estimating relation between echo signal and far-end signal and controlling adaptive filtering convergence
Figure FDA00032756400000000112
The relationship is as follows:
Figure FDA00032756400000000113
Figure FDA00032756400000000114
s5, constructing an acoustic echo cancellation ICA model based on the ICA idea, wherein the model equation can be expressed as:
Figure FDA0003275640000000021
wherein the content of the first and second substances,
Figure FDA0003275640000000022
in order to obtain the desired original signal,
Figure FDA0003275640000000023
in order to observe the vector, the vector is,
Figure FDA0003275640000000024
is a mixing matrix;
s6, an equation for separating the original signals can be established according to S5, which can be expressed as follows:
Figure FDA0003275640000000025
wherein the content of the first and second substances,
Figure FDA0003275640000000026
is a non-0 scalar to obtain
Figure FDA0003275640000000027
S7 solving by Fast ICA method
Figure FDA0003275640000000028
In order to separate the target voice, the specific steps are as follows:
(a) to observation data matrix
Figure FDA0003275640000000029
Carrying out equalization;
(b) is provided with
Figure FDA00032756400000000210
Whitening observation data matrix x (Z ═ vx), where v ═ D-1/2ETD, E are feature values and feature vectors corresponding to the covariance matrix of the observation data matrix x respectively;
(c) selecting the number of components to be separated of ICA, and setting a counter l to be 1;
(d) setting initial random weight coefficients
Figure FDA00032756400000000211
(e) Update solving
Figure FDA00032756400000000212
(f) Decorrelation:
Figure FDA00032756400000000213
(g) normalization weight coefficient:
Figure FDA00032756400000000214
(h) if it is not
Figure FDA00032756400000000215
Non-convergence
Figure FDA00032756400000000216
Returning to the step (e);
(i) iteration l ═ l +1, if l ≦ m, return to step (d);
s8, for the j +1 th channel, the weight coefficient obtained by S07
Figure FDA00032756400000000217
And approximating echo cancellation of other channels, wherein the equation is as follows:
Figure FDA00032756400000000218
the estimated calculation formula for the near-end signals in the other microphone channel signals is as follows:
Figure FDA0003275640000000031
2. an acoustic echo cancellation device facing a microphone array, characterized by: including central processing module, collection module, storage module, power module, host computer communication module, module and keying module reset, central processing module is used for control collection module and processing the signal that collection module gathered, storage module is used for the storage central processing module input storage module's signal and storage module to the signal that central processing module exported, host computer communication module is used for handling the warp the signal that central processing module handled and control central processing module, the module that resets is used for controlling central processing module's reset, keying module be used for to central processing module input parameter adopts claim 1 the acoustic echo cancellation method towards microphone array eliminate the echo.
3. The microphone array-facing acoustic echo cancellation device of claim 2, wherein: the central processing module is an OMAP dual-core processor based on an ARM core and a DSP core, and the acquisition module is a microphone array data acquisition module.
4. An acoustic echo cancellation device facing a microphone array according to claim 3, characterized in that: the upper computer communication module further comprises a cloud server for voice recognition.
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