LPC.rar_LPC_lpc matlab

function enhancedsignal=wiener(noisyspeech,samplefrequency) x=noisyspeech; fs=samplefrequency; nx=length(x); enhanced_x=zeros(1,nx); %分帧和加窗 FrameLen=fix(0.025*fs);%取25毫秒为一帧 overlap=FrameLen/2; inc=FrameLen-overlap; %帧移 x_frame=enframe(x,FrameLen,inc); %分帧 nf=size(x_frame,1); % 帧数 win=hamming(FrameLen)'; x_window=[]; for k=1:nf x_row=x_frame(k,:).*win; % 加窗 x_window=[x_window;x_row]; end %对带噪语音进行DFT y=fft(x_window'); ymag = abs(y); yphase = angle(y); %初始噪声估计 NNoise=23; %取噪音段（语音的初始段）帧数 MN=mean(ymag(:,1:NNoise)')'; PN=mean(ymag(:,1:NNoise)'.^2)'; %初始噪声功率谱均值 NoiseCounter=0;%连续噪声段长度 SmoothFactor=9;%噪声平滑因子 Alpha=0.95; %语音平滑因子 SNRPre=ones(size(MN)); %维纳滤波 for k=1:nf %-----噪声估计更新 if k<=NNoise SpeechFlag=0;%非有声段 NoiseCounter=NNoise; else NoiseMargin=3; HangOver=8; SpectralDist= 20*(log10(ymag(:,k))-log10(MN)); SpectralDist(find(SpectralDist<0))=0; Dist=mean(SpectralDist); if (Dist < NoiseMargin) NoiseFlag=1; NoiseCounter=NoiseCounter+1; else NoiseFlag=0; NoiseCounter=0; end % 只检测大于一定长度的噪声段 if (NoiseCounter > HangOver) SpeechFlag=0; else SpeechFlag=1; end end if SpeechFlag==0 % 如果是噪声段 MN=(SmoothFactor*MN+ymag(:,k))/(SmoothFactor+1); %更新噪声均值 PN=(SmoothFactor*PN+(ymag(:,k).^2))/(1+SmoothFactor); %更新噪声功率 end %------滤波 SNRNew=(ymag(:,k).^2)./PN-1; SNRPost=Alpha*SNRPre+(1-Alpha).*max(SNRNew,0); %由上一帧的增益，原始语音，噪声功率求得SNR，再平滑并确定SNR Gain=SNRPost./(SNRPost+1); smag=Gain.*ymag(:,k); SNRPre=smag.^2./PN; %备下一帧用 %------重新生成谱 spectrum= smag.*exp(j*yphase(:,k)); %------重新生成语音 enhanced_x((inc*(k-1)+1):(inc*(k-1)+FrameLen))=enhanced_x((inc*(k-1)+1):(inc*(k-1)+FrameLen))+real(ifft(spectrum,FrameLen))'; end enhancedsignal=enhanced_x;