语音信号的频谱分析实验报告

1一、试验内容波形和频谱图；在语音信号中增加正弦噪声信号(自己设置几个频率的正弦信号)，对参加噪画出滤波后信号的时域波形和频谱，并对滤波前后的信号进展比照试听，分析信号的变化。二、实现步骤1．语音信号的采集利用s下的录音机，录制一段自己的话音，时间在3s内。Matlabwavread对语音信号进展采样4kHz。[y,fs,bits]=wavread(”j.wav”,[102463500]);sound(y,fs,bits);2．语音信号的频谱分析要求首先画出语音信号的时域波形；然后对语音号进展傅里叶变换，得到信号的频谱特性。在采集得到的语音信号中参加正弦噪声信号〔频率为10kH，然后对参加噪声信号后的语音号进展傅里叶变换，得到信号的频谱特性。并利用sound试听前后语音信号的不同。3.设计滤波器sound试听滤波前后语音信号的不同。1、语音信号的采集[y,fs,bits]=wavread(”j.wav”,[102463500]);sound(y,fs,bits);2、语音信号的频谱分析Y=fft(y,4096);figure(1);plot(y);title(”语音信号的时域波形”);figure(2);plot(abs(Y));title(”语音信号的频谱特性”);IIR数字滤波器低通clear;closeall;[y,fs,bits]=wavread(”j.wav”,[102463500]);Y=fft(y,4096);fb=1000;fc=1200;As=100;Ap=1;fs=22050;wc=2*fc/fs;wb=2*fb/fs;[n,wn]=ellipord(wc,wb,Ap,As);[b,a]=ellip(n,Ap,As,wn);figure(1);freqz(b,a,512,fs);x=filter(b,a,y);X=fft(x,4096);figure(2);subplot(2,2,1);plot(y);title(”滤波前信号波形”);subplot(2,2,2);plot(abs(Y));title(”滤波前信号频谱”);Subplot(2,2,3);plot(x);title(”滤波后信号波形”);Subplot(2,2,4);plot(abs(X));title(”滤波后信号频谱”);sound(x,fs,bits);IIR高通wp=2*pi*4800/18000;wr=2*pi*5000/18000;Ap=1;Ar=15;T=1[N,wn]=buttord(wp/pi,wr/pi,Ap,Ar);[b,a]=butter(N,wn,”high”);[db,mag,pha,grd,w]=freqz_m(b,a);subplot(211);plot(w/pi,mag);title(”数字巴特沃茨高通滤波器幅度响应|Ha(J\Omega)|”);subplot(212);plot(w/pi,db);title(”数字巴特沃茨高通滤波器幅度响应(db)”);[y,Fs,nbite]=wavread(”j.wav”,[102463500]);Y=fft(y,4096);x=filter(b,a,y);X=fft(x,4096);figure(3)subplot(211);plot(y);title(”原时域波形”);subplot(212);plot(x);title(”滤波后信号波形”);figure(4)subplot(211);plot(abs(Y));title(”原频谱频谱”);subplot(212);plot(abs(X));title(”滤波后信号频谱”);sound(x,Fs);IIR带通wp=[1200*pi*2/9000,3000*2*pi/9000];wr=[1000*2*pi/9000,3200*2*pi/9000];Ap=1;Ar=100;[N,wn]=buttord(wp/pi,wr/pi,Ap,Ar);[b,a]=butter(N,wn,”bandpass”);[db,mag,pha,grd,w]=freqz_m(b,a);subplot(211);plot(w/pi,mag);title(”数字巴特沃茨带通滤波器幅度响应|Ha(J\Omega)|”);subplot(212);plot(w/pi,db);title(”数字巴特沃茨带通滤波器幅度响应(db)”);[y,Fs,nbite]=wavread(”j.wav”);Y=fft(y,4096);x=filter(b,a,y);X=fft(x,4096);figure(3)subplot(211);plot(y);title(”原时域波形”);subplot(212);plot(x);title(”滤波后信号波形”);figure(4)subplot(211);plot(abs(Y));title(”原频谱频谱”);subplot(212);plot(abs(X));title(”滤波后信号频谱”);sound(x,Fs);FIR数字滤波器FIR低通fsamp=8000;rp=1;rs=100;fcuts=[10001200];d1=(10^(rp/20)-1)/(10^(rp/20)+1);d2=10^(-rs/20);mags=[10];devs=[d1d2];[n,wn,beta,ftype]=kaiserord(fcuts,mags,devs,fsamp);hh=fir1(n,wn,ftype,kaiser(n+1,beta),”noscale”);freqz(hh);[y,Fs,nbite]=wavread(”j.wav”);Y=fft(y,4096);x=fftfilt(hh,y);X=fft(x,4096);figure(2)subplot(211);plot(y);title(”原时域波形”);subplot(212);plot(x);title(”滤波后信号波形”);figure(3)subplot(211);plot(abs(Y));title(”原频谱频谱”);subplot(212);plot(abs(X));title(”滤波后信号频谱”);sound(x,Fs);FIR高通wc=2*pi*4800;wp=5000*2*pi/18000;f=[0.5333,0.5556];m=[0,1];rp=1;rs=100;d1=(10^(rp/20)-1)/(10^(rp/20)+1);d2=10^(-rs/20);rip=[d2,d1];[N,fo,mo,w]=remezord(f,m,rip);N=N+2;hn=remez(N,fo,mo,w);[hw,w]=freqz(hn,1);plot(w/pi,20*log10(abs(hw)));[y,Fs,nbite]=wavread(”j.wav”);Y=fft(y,4096);x=fftfilt(hn,y);X=fft(x,4096);figure(2)subplot(211);plot(y);title(”原时域波形”);subplot(212);plot(x);title(”滤波后信号波形”);figure(3)subplot(211);plot(abs(Y));title(”原频谱频谱”);subplot(212);plot(abs(X));title(”滤波后信号频谱”);sound(x,Fs);FIR带通wp1=2*pi*1200/8000;wp2=3000*2*pi/8000;wc1=2*pi*1000/8000;wc2=2*pi*3200*8000;f=[0.25,0.30,0.75,0.80][n,wn,bta,ftype]=kaiserord([0.25,0.30,0.75,0.80],[010],[0.010.10870.01]);h1=fir1(n,wn,ftype,kaiser(n+1,bta),”noscale”);[hh1,w1]=freqz(h1,1,256);figure(1);plot(w1/pi,20*log10(abs(hh1)));grid;[y,Fs,nbite]=wavread(”j.wav”);Y=fft(y,4096);x=fftfilt(h1,y);X=fft(x,4096);figure(2)subplot(211);plot(y);title(”原时域波形”);subplot(212);plot(x);title(”滤波后信号波形”);figure(3)subplot(211);plot(abs(Y));title(”原频谱频谱”);subplot(212);plot(abs(X));title(”滤波后信号频谱”);sound(x,Fs);设计结果分析语音分析12Fs=22050；n=4096IR低通3滤波器在通带内平滑，通带截止频率为1000hz，最大衰减0dB；阻带起始频率为1200hz，最小衰减100dB；相位不是线性变化,根本满足性能要求.4语音信号经过低通滤波器后，根本没发生变化IIR高通5数字滤波器在通带内平滑，通带截止频率为0.5π，最大衰减0dB；阻带起始频率为0.48π，最小衰减100dB；相位不是线性变化,根本满足性能要求.语言信号经过6IIR带通7通带范围为0.2，0