【语音去噪】基于谱减法、最小均方和维纳滤波三种算法实现语音去噪含Matlab源码

1 简介

语音信号在实际场合中通常容易受噪声的干扰,较强的噪声会降低语音识别的效率,为了使语音信号可懂,需要对噪声进行处理.本文先分析了语音和噪声的特性,介绍了谱减法、最小均方和维纳滤波三种语音去噪算法,以及这些算法实现的仿真结果对比。

2 部分代码

function [ss,po]=specsubm(s,fs,p)%SPECSUBM performs speech enhancement using spectral subtraction [SS,PO]=(S,FS,P)%% implementation of spectral subtraction algorithm by R Martin (rather slow)% algorithm parameters: t* in seconds, f* in Hz, k* dimensionless% 1: tg = smoothing time constant for signal power estimate (0.04): high=reverberant, low=musical% 2: ta = smoothing time constant for signal power estimate%        used in noise estimation (0.1)% 3: tw = fft window length (will be rounded up to 2^nw samples)% 4: tm = length of minimum filter (1.5): high=slow response to noise increase, low=distortion% 5: to = time constant for oversubtraction factor (0.08)% 6: fo = oversubtraction corner frequency (800): high=distortion, low=musical% 7: km = number of minimisation buffers to use (4): high=waste memory, low=noise modulation% 8: ks = oversampling constant (4)% 9: kn = noise estimate compensation (1.5)% 10:kf = subtraction floor (0.02): high=noisy, low=musical% 11:ko = oversubtraction scale factor (4): high=distortion, low=musicalif nargin<3 po=[0.04 0.1 0.032 1.5 0.08 400 4 4 1.5 0.02 4].'; else po=p; endns=length(s);ts=1/fs;ss=zeros(ns,1);​ni=pow2(nextpow2(fs*po(3)/po(8)));ti=ni/fs;nw=ni*po(8);nf=1+floor((ns-nw)/ni);nm=ceil(fs*po(4)/(ni*po(7)));​win=0.5*hamming(nw+1)/1.08;win(end)=[];zg=exp(-ti/po(1));za=exp(-ti/po(2));zo=exp(-ti/po(5));​px=zeros(1+nw/2,1);pxn=px;os=px;mb=ones(1+nw/2,po(7))*nw/2;im=0;osf=po(11)*(1+(0:nw/2).'*fs/(nw*po(6))).^(-1);​imidx=[13 21]';x2im=zeros(length(imidx),nf);osim=x2im;pnim=x2im;pxnim=x2im;qim=x2im;​for is=1:nf   idx=(1:nw)+(is-1)*ni;   x=rfft(s(idx).*win);   x2=x.*conj(x);      pxn=za*pxn+(1-za)*x2;   im=rem(im+1,nm);   if im      mb(:,1)=min(mb(:,1),pxn);   else      mb=[pxn,mb(:,1:po(7)-1)];   end   pn=po(9)*min(mb,[],2);   %os= oversubtraction factor   os=zo*os+(1-zo)*(1+osf.*pn./(pn+pxn));      px=zg*px+(1-zg)*x2;   q=max(po(10)*sqrt(pn./x2),1-sqrt(os.*pn./px));    ss(idx)=ss(idx)+irfft(x.*q);   endif nargout==0   soundsc([s; ss],fs);end​​​​​

3 仿真结果

4 参考文献

[1]吴马军, 俞兴莉, 陈亮. 语音降噪算法的实现研究[J]. 信息通信, 2019, 000(001):72-74.​

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