卡曼滤波法在语音处理上的应用【Matlab语音处理】.zip

%%%基于LPC全极点模型的最大后验概率估计法,采用维纳滤波 clear clc [x,Fs4,bits4] = wavread('D:\yuyin\speech_noisy2_8k.wav'); N=256; %帧长 m=N/2; %每帧移动的距离 lenth=length(x); %输入信号的长度 count=floor(lenth/m)-2; %处理整个信号需要移动的帧数%%%先不考虑补零的问题 s=1; %从第s帧开始 p=11; a=zeros(1,p); w=hamming(N); y_temp=0; F=zeros(11,11); F(1,2)=1; F(2,3)=1; F(3,4)=1; F(4,5)=1; F(5,6)=1; F(6,7)=1; F(7,8)=1; F(8,9)=1; F(9,10)=1; F(10,11)=1; H=zeros(1,p); S0=zeros(p,1); P0=zeros(p); S=zeros(p); H(11)=1; s=zeros(N,1); G=H'; P=zeros(p); y_temp=cov(x(1:7680)); x_frame=zeros(256,1); x_frame1=zeros(256,1); T=zeros(lenth,1); for r=1:count x_frame=x((r-1)*m+1:(r+1)*m); if r==1 [a,VS]=lpc(x_frame(:),p); else [a,VS]=lpc(T((r-2)*m+1:(r-2)*m+256),p); end if (VS-y_temp>0) VS=VS-y_temp; else VS=0.0005; end F(p,:)=-1*a(p+1:-1:2); % if r==1 % S=[zeros(p,1)]; %state vector % P0=[zeros(p,p)]; %error covatiance % else % % P0=P; % end for j=1:256 if(j==1) S=F*S0; Pn=F*P*F'+G*VS*G'; else S=F*S; Pn=F*P*F'+G*VS*G'; end K=Pn*H'*(y_temp+H*P*H').^(-1); P=(eye(p)-K*H)*Pn; S=S+K*[x_frame(j)-H*S]; T((r-1)*m+j)=H*S; end %开始循环计算LPC参数 end rt=137.78/128; x=T./rt; wavwrite(x,Fs4,bits4,'d:\LPC_3111.wav'); display('ok')