基于DTW语音识别matlab代码

function [StartPoint,EndPoint]=vad(k,fs) %% [StartPoint,EndPoint]=vad(k,fs) %% 语音信号端点检测程序，k为语音信号， %% fs为其采样频率，程序绘制出语音信号 %% 相关波形图并返回起止端点所对帧号 close all; % 幅度归一化到[-1,1] k=double(k); k=k./max(abs(k)); %------------------------------ % 显示波形 %------------------------------ disp('显示原始波形图……'); t=0:1/fs:(length(k)-1)/fs; subplot(3,1,1); plot(t,k); axis([0,(length(k)-1)/fs,min(k),max(k)]); title('(I) 语音信号波形'); xlabel('Time:s'); ylabel('Amplitude(normalized)'); disp('显示语音起始处放大波形图……'); t1=0.2:1/fs:0.3; k1=k(0.2*fs:0.3*fs); subplot(3,1,2); plot(t1,k1); axis([0.2,0.3,min(k),max(k)]); title('(II) 语音起始处放大波形图'); xlabel('Time:s'); ylabel('Amplitude(normalized)'); disp('显示语音结束处放大波形图……'); t1=0.4:1/fs:0.5; k1=k(0.4*fs:0.5*fs); subplot(3,1,3); plot(t1,k1); axis([0.4,0.5,min(k),max(k)]); title('(III) 语音结束处放大波形图'); xlabel('Time:s'); ylabel('Amplitude(normalized)'); %------------------------------ % 计算短时过零率 %------------------------------ FrameLen=240; FrameInc=80; FrameTemp1=enframe(k(1:end-1),FrameLen,FrameInc); FrameTemp2=enframe(k(2:end),FrameLen,FrameInc); signs=(FrameTemp1.*FrameTemp2)<0; diffs=abs(FrameTemp1-FrameTemp2)>0.01; zcr=sum(signs.*diffs,2); disp('显示原始波形图……'); figure,subplot(3,1,1); plot(t,k); axis([0,(length(k)-1)/fs,min(k),max(k)]); title('(I) 语音信号波形'); xlabel('Time:s'); ylabel('Amplitude(normalized)'); disp('显示过短时零率……') zcrInd=1:length(zcr); subplot(3,1,2); plot(zcrInd,zcr); axis([0,length(zcr),0,max(zcr)]); title('(II) 短时过零率'); xlabel('Frame'); ylabel('Zcr'); %------------------------------ % 计算短时能量 %------------------------------ amp=sum(abs(enframe(filter([1 -0.9375], 1, k), FrameLen, FrameInc)), 2); disp('显示短时能量……') ampInd=1:length(amp); subplot(3,1,3); plot(ampInd,amp); axis([0,length(amp),0,max(amp)]); title('(III) 短时能量'); xlabel('Frame'); ylabel('Energy'); %------------------------------ % 设置门限 %------------------------------ disp('设置门限……'); ZcrLow=max([round(mean(zcr)*0.1),3]); %过零率低门限 ZcrHigh=max([round(max(zcr)*0.1),5]); %过零率高门限 AmpLow=min([min(amp)*10,mean(amp)*0.2,max(amp)*0.1]); %能量低门限 AmpHigh=max([min(amp)*10,mean(amp)*0.2,max(amp)*0.1]); %能量高门限 %------------------------------ % 端点检测 %------------------------------ MaxSilence=8; %最长语音间隙时间 MinAudio=16; %最短语音时间 Status=0; %状态：0静音段,1过渡段,2语音段,3结束段 HoldTime=0; %语音持续时间 SilenceTime=0; %语音间隙时间 disp('开始端点检测……'); for n=1:length(zcr) switch Status case{0,1} if amp(n)>AmpHigh | zcr(n)>ZcrHigh StartPoint=n-HoldTime; Status=2; HoldTime=HoldTime+1; SilenceTime=0; elseif amp(n)>AmpLow | zcr(n)>ZcrLow Status=1; HoldTime=HoldTime+1; else Status=0; HoldTime=0; end case 2, if amp(n)>AmpLow | zcr(n)>ZcrLow HoldTime=HoldTime+1; else SilenceTime=SilenceTime+1; if SilenceTime<MaxSilence HoldTime=HoldTime+1; elseif (HoldTime-SilenceTime)<MinAudio%噪音，重新开始 Status=0; HoldTime=0; SilenceTime=0; else Status=3;%声音结束 end end case 3, break; end if Status==3 break; end end HoldTime=HoldTime-SilenceTime; EndPoint=StartPoint+HoldTime; disp('显示端点……'); figure,subplot(3,1,1); plot(k); axis([1,length(k),min(k),max(k)]); title('(I) 语音信号'); xlabel('Sample'); ylabel('Speech'); line([StartPoint*FrameInc,StartPoint*FrameInc],[min(k),max(k)],'color','red'); line([EndPoint*FrameInc,EndPoint*FrameInc],[min(k),max(k)],'color','red'); subplot(3,1,2); plot(zcr); axis([1,length(zcr),0,max(zcr)]); title('(II) 短时过零率'); xlabel('Frame'); ylabel('ZCR'); line([StartPoint,StartPoint],[0,max(zcr)],'Color','red'); line([EndPoint,EndPoint],[0,max(zcr)],'Color','red'); subplot(3,1,3); plot(amp); axis([1,length(amp),0,max(amp)]); title('(III) 短时能量'); xlabel('Frame'); ylabel('Energy'); line([StartPoint,StartPoint],[0,max(amp)],'Color','red'); line([EndPoint,EndPoint],[0,max(amp)],'Color','red');