weina1.m

matlab仿真通过的降噪程序

clear all;
[y1,fs,bits]=wavread('F:\noise enhancing\wav\5.wav');
y1=y1/max(abs(y1));%语音信号归一化
%wavwrite(y1,8000,8,'D:\语音降噪\wav\4.wav');
figure(1);
plot(y1);

[noise,fs1,bits1]=wavread('F:\noise enhancing\wav\5_noise.wav');
y=mixsig(y1,noise,0);% 混合
y=y/max(abs(y));%归一化
wavwrite(y,8000,8,'F:\noise enhancing\wav\mymasking_s&w(0).wav');%0db带噪信号
figure(2);
plot(y);
%clear all;
%[y1,fs,bits]=wavread('8k8bit.wav'); % Actual Signal
%[noise,fs1,bits1]=wavread('8k8bit_noise.wav');
%y=mixsig(y1,noise, 10);
%wavwrite(y,8000,8,'f:\a\mymasking_s&w.wav');
%figure(1);
%plot(y);
frame = 256;    % Defining frame size
%for k = 1:2560, % Loop for first 50 frames(0.5 seconds) of noise
%  y_temp(k) = y(k);
%end;
shift=128;
win=hamming(256);
%a=length(y),a=18800
for j1 = 1:length(y),
 signal(j1) = y(j1);
end;

ps_noise=zeros(length(signal)/frame,frame);
frame_temp = zeros(length(signal)/frame,frame);
%length1 = length(y_temp);   % length of the noise samples(first 4000 samples)
%ps_noise = zeros(length1/frame,frame);
%frame_temp = zeros(length1/frame,frame);
%hh = 0; 
 %  for k = 1 : length1/frame,
 %       for l = 1 : frame,
%          b(l) = y_temp(hh+l);
%        end;
%        hh = hh + frame;
%        frame_temp(k,1:frame) = fft(b);                      %fft for the first 50 frames
%        ps_noise(k,1:frame) = (frame_temp(k,1:frame).*conj(frame_temp(k,1:frame)))/frame;
%        A(1,k) = (sum(ps_noise(k,1:frame)));          % Sum of the power spectral densities of samples within a frame

%  end;
%threshold = sum(A)*frame/length1;            % setting the threshold for the noise(frame noise)

hh = 0; 
   for k = 1 : 5,
       for l = 1 : frame,
          b(l) = signal(hh+l);
      end;
        hh = hh + frame;
        frame_temp(k,1:frame) = abs(fft(b));                      %fft for the first 50 frames
        ps_noise(k,1:frame) = (frame_temp(k,1:frame).*conj(frame_temp(k,1:frame)))/frame;
        %ps_noise(1,1:frame)= (sum(ps_noise(1:k,l))/20);          % Sum of the power spectral densities of samples within a frame

    end;%语音前五真早声能量
    %ps_noise=zeros(length(signal)/frame,frame);
    %ps_noise(1,1:frame)= sum(A)/20;            % setting the threshold for the noise(frame noise)
    ps_noise(1,1:frame)= (sum(ps_noise(1:k,1:frame))/5);



%
head = 0; 
mm=1;
nn=1;
% START OF THE NOISE ELIMINATION THROUGH SPECTRAL SUBTRACTION BASED ON THE THRESHOLD SET

   for k = 1 : length(signal)/frame,
        for m = 1 : frame,
          abc1(m) = signal(head+m);
          %abc1=abc1.*win';
        end;
        
        head = head +frame;
        frame_temp(k,1:frame) = abs(fft(abc1));% FFT OF THE SIGNAL + NOISE FRAME BY FRAME

        frame_angle(k,1:frame) = angle(fft(abc1));% ANGLE OF FFT OF THE SIGNAL + NOISE FRAME BY FRAME

        ps_signal(k,1:frame) = (frame_temp(k,1:frame).*conj(frame_temp(k,1:frame)))./frame;
        
        %ps_temp=zeros(1,frame);
        ps_temp(k,1:frame)=ps_signal(k,1:frame);
        
        
        if k==1
            ps_noise(k,1:frame)=0.98*ps_noise(1,1:frame)+0.02*ps_signal(k,1:frame);
           % ps_signal(k,1:frame)=0.98*ps_signal(k,1:frame)+0.02*ps_signal(k,1:frame);
        else
           ps_noise(k,1:frame)=ps_noise(1,1:frame);%0.99*ps_noise(1,1:frame)+0.01*ps_signal(k,1:frame);
           ps_signal(k,1:frame)=ps_signal(k,1:frame);%0.99*ps_signal(k,1:frame)+0.01*ps_noise(1,1:frame);%+0.01*ps_signal(k-1,1:frame);
        end
        frame_ps(1,k) = (sum(ps_signal(k,1:frame)));%一阵内信号能量之和
        frame_pn(1,k)=sum(ps_noise(k,1:frame));
        %ps_final(1,k) = frame_ps(1,k) - threshold;
        %aa=0.8;
        ps_final(1,k) = frame_ps(1,k)- frame_pn(1,k); 
        
     %短点检测
    %    yeta(1,k)=sum(    ps_signal(k,1:frame)/(abs(ps_signal(k,1:frame)-ps_noise(k,1:frame))) );
        %yeta(1,k)=frame_ps(1,k)/(frame_ps(1,k)- frame_pn(1,k));
     %  if(yeta(1,k)>40),
          % ps_final(1,k) =0.1;
           % else 
           %if(yeta(1,k)>1)
            %   ps_final(1,k)=(abs(frame_ps(1,k)-frame_pn(1,k)));
            %else
           %if ps_final(1,k)< 0,
            %ps_final(1,k) =0.1;
            %else
            % ps_final(1,k) = ps_final(1,k); 
             
            %end;
            %end;
            %end;
       
        aa=0.7;bb=2;
        h(1,k)=power(ps_final(1,k)/(ps_final(1,k)+aa*frame_pn(1,k)),bb);
        frame1(k,1:frame) = h(1,k).*(frame_temp(k,1:frame));%为那滤波
        
       frame1(k,1:frame) = frame1(k,1:frame).*(exp(i*frame_angle(k,1:frame)));
        frame2(k,1:frame)=ifft(frame1(k,1:frame));
        signal(1,(((k-1)*frame)+1):(k*frame)) = frame2(k,1:frame); % Retriving back the signal(after spectral subtraction)
    end     
   
 signal((length(y)-1000):(length(y)))=[];   %give up 4 frames in the end
 y1((length(y1)-1000):(length(y1)))=[];
figure(3);
plot(1:length(frame_ps),frame_ps,1:length(ps_final),ps_final);
figure(4);
signal=signal';
signal=signal/max(abs(signal));%归一化
plot(1:length(signal),signal);
%以下画语谱图
%map=(log10(1:0.1:10))';
%map=[map map map ];
%subplot(2,2,1)
%spgrambw( noise,8000);title('noise Specgram');colormap(1-map);
%subplot(2,2,2)
%spgrambw(y1,8000);title('sig Specgram');colormap(1-map);
%subplot(2,2,3)
%spgrambw(y,8000);title('mixsig Specgram');colormap(1-map);
%subplot(2,2,4)
%spgrambw(signal,8000);title('Proposed Algorithm Specgram');colormap(1-map);

%spgrambw(sig,8000);title('pure Specgram');colormap(1-map);
%[overall_snr2,seg_nr2]=snr(y1,signal)
overall_snr = 10*log10(sum(abs(y1).^2)/sum((abs(y1-signal)).^2))
wavwrite(signal,8000,8,'F:\noise enhancing\wav\mymasking21(0db).wav');