语音信号处理实验报告

语音信号处理实验报告【实验一】实验题目Shorttimeanalysis实验要求WriteaMATLABprogramtoanalyzeaspeechandsimultaneously,onasinglepage,plotthefollowingmeasurements:1.theentirespeechwaveform2.theshort-timeenergy,En3.theshort-timemagnitude,Mn4.theshort-timezero-crossing,Zn5.thenarrowbandspectrogram6.thewidebandspectrogramUseboththespeechwaveformsinthewznjdx_normal.wav.Chooseappropriatewindowsizes,windowshifts,andwindowfortheanalysis.Explainyourchoiceoftheseparameters.实验程序clear[x,fs]=wavread('wznjdx_normal.wav');n=length(x);N=320;subplot(4,1,1);plot(x);h=linspace(1,1,N);En=conv(h,x.*x);subplot(4,1,2);plot(En);Mn=conv(h,abs(x));subplot(4,1,3);plot(Mn);fori=1:n-1ifx(i)>=0y(i)=1;elsey(i)=-1;endifx(i+1)>=0y(i+1)=1;elsey(i+1)=-1;endw(i)=abs(y(i+1)-y(i));endk=1;j=0;while(k+N-1)<nZm(k)=0;fori=0:N-1Zm(k)=Zm(k)+w(k+i);endj=j+1;k=k+N/2;endforw=1:jQ(w)=Zm(160*(w-1)+1)/(2*N);endsubplot(4,1,4);plot(Q);grid;figure(2);subplot(2,1,1);spectrogram(x,h,256,200,0.0424*fs);subplot(2,1,2);spectrogram(x,h,256,200,0.0064*fs);实验结果语谱图：（Matlab7.0用不了spectrogram）【实验二】实验题目Homomorphicanalysis实验要求WriteaMATLABprogramtocomputetherealcepstrumsofasectionofvoicedspeechandunvoicedspeech.Plotthesignal,thelogmagnitudespectrum,therealcepstrum,andthelowpasslifteredlogmagnitudespectrum.三、实验程序nfft=256;[x,fs]=wavread('wznjdx_normal.wav');fx=x;Xvm=log(abs(fft(fx,nfft)));xhv=real(ifft(Xvm,nfft));lifter=zeros(1,nfft);lifter(1:30)=1;lifter(nfft-28:nfft)=1;fnlen=0.02*fs;%20mswin=hamming(fnlen);%加窗n=fnlen;%窗宽度赋给循环自变量nnoverlap=0.5*fnlen;while(n<=length(x)-1)fx=x(n-fnlen+1:n).*win;n=n+noverlap;endxhvp=xhv.*lifter';figure;subplot(4,1,1)plot(lifter);title('倒谱滤波器');subplot(4,1,2)plot(x);title('语音信号波形');subplot(4,1,3)plot(Xvm);title('Xvm');subplot(4,1,4)plot(xhv);title('xhv');四、实验结果【实验三】一、实验题目LPanalysis二、实验要求WriteaMATLABprogramtoconvertfromaframeofspeechtoasetoflinearpredictioncoefficients.PlottheLPCspectrumsuperimposedonthecorrespondingSTFT.三、实验程序clear;[x,fs]=wavread('wznjdx_normal.wav');fx=x(4000:4160-1);p=10;[a,e,k]=aryule(fx,p);G=sqrt(e*length(fx));f=log(abs(fft(fx)));h0=zeros(1,160);h=log(G)-log(abs(fft(a,160)));figure(1);subplot(211);plot(fx);subplot(212);plot(f);holdon;plot((0:160-1),h,'r');四、实验结果【实验四】一、实验题目Pitchestimation二、实验内容Writeaprogramtoimplementthepitchestimationandthevoiced/unvoiceddecisionusingtheLPC-basedmethod.三、实验程序clear[x,fs]=wavread('wznjdx_normal.wav');n=length(x);Q=x';NFFT=512;N=256;Hamm=hamming(N);frame=30;M=Q(((frame-1)*(N/2)+1):((frame-1)*(N/2)+N));Frame=M.*Hamm';%lowpassfilter[b2,a2]=butter(2,900/4000);speech2=filter(b2,a2,Frame);%filter%residual[a,e]=lpc(speech2,20);errorlp=filter(a,1,speech2);%residual%Short-termautocorrelation.re=xcorr(errorlp);%Findmaxautocorrelationforlagsintheintervalminlagtomaxlag.minlag=17;%F0:450Hzmaxlag=160;%F0:50Hzfnlen=256;[remax,idx]=max(re(fnlen+minlag:fnlen+maxlag));figuresubplot(3,1,1);plot(Frame);subplot(3,1,2);plot(speech2);subplot(3,1,3);plot(re);text(500,0,'idx');idx=idx-1+minlagremax四、实验结果【实验五】一、实验题目Speechsynthesis二、实验内容WriteaprogramtoanalyzeaspeechandsynthesizeitusingtheLPC-basedmethod.三、实验程序主程序clear;[x,sr]=wavread('wznjdx_normal.wav');p=[1-0.9];x=filter(p,1,x);N=256;inc=128;y=lpcsyn(x,N,inc);wavplay(y,sr);子程序lpcsynfunctiony=lpcsyn(x,N,inc)%[x,sr]=wavread('wznjdx_normal.wav');%pre=[1-0.97];%x=filter(pre,1,x);%N=256;%inc=128;fn=floor(length(x)/inc);y=zeros(1,50000);for(i=1:fn)order=16;x(1:N,i)=x((i-1)*inc+1:(i+1)*inc);[A(i,:),G(i),P(i),fnlen,fnshift]=lpcana(x(1:N,i),order);if(P(i))%Voicedframe.e=zeros(N,1);e(1:P(i):N)=1;%Impulse-trainexcitation.else%Unvoicedframe.e=randn(N,1);%Whitenoiseexcitation.endyt=filter(G(i),A(i,:),e);j=(i-1)*inc+[1:N];y(j)=y(j)+yt';end;end子程序lpcanafunction[A,G,P,fnlen,fnshift]=lpcana(x,order)fnlen=256;fnshift=fnlen/2;n=length(x);[b2,a2]=butter(2,900/4000);speech2=filter(b2,a2,x);[A,e]=lpc(speech2,order);errorlp=filter(A,1,speech2);re=xcorr(errorlp);G=sqrt(e*length(speech2));minlag=17;maxlag=160;[remax,idx]=max(re(n+minlag:n+maxlag));P=idx-1+minlag;end四、实验结果【实验六】一、实验题目Speechenhancement二、实验内容Writeaprogramtoimplementthebasicspectralmagnitudesubtraction.三、实验程序clear[speech,fs,nbits]=wavread('wznjdx_normal.wav');%读入数据alpha=0.04;%噪声水平winsize=256;%窗长size=length(speech);%语音长度numofwin=floor(size/winsize);%帧数hamwin=zeros(1,size);%定义汉明窗长度enhanced=zeros(1,size);%定义增强语音的长度ham=hamming(winsize)';%%产生汉明窗x=speech'+alpha*randn(1,size);%信号加噪声noisy=alpha*randn(1,winsize);%噪声估计N=fft(noisy);nmag=abs(N);%噪声功率谱%分帧forq=1:2*numofwin-1frame=x(1+(q-1)*winsize/2:winsize+(q-1)*winsize/2);%对带噪语音帧间重叠一半取值hamwin(1+(q-1)*winsize/2:winsize+(q-1)*winsize/2)=...hamwin(1+(q-1)*winsize/2:winsize+(q-1)*winsize/2)+ham;%加窗y=fft(frame.*ham);mag=abs(y);%带噪语音功率谱phase=angle(y);%带噪语音相位%幅度谱减fori=1:winsizeifmag(i)-nmag(i)>0clean(i)=mag(i)-nmag(i);elseclean(i)=0;endend%频域中重新合成语音spectral=clean.*exp(j*phase);%反傅里叶变换并重叠相加enhanced(1+(q-1)*winsize/2:winsize+(q-1)*winsize/2)=...enhanced(1+(