evrc_alg1.m

matlab仿真通过的降噪程序

clear all;
[y1,fs,bits]=wavread('F:\noise enhancing\wav\5.wav');
%[y1,fs,bits]=wavread('F:\语音降噪\wav\female.wav');
y1=y1/max(abs(y1));%语音信号归一化
wavwrite(y1,8000,8,'F:\noise enhancing\voise\5.wav');
%wavwrite(y1,8000,8,'F:\语音降噪\wav\sunshine2.wav');
figure(1);
plot(y1);

[noise,fs1,bits1]=wavread('F:\noise enhancing\wav\5_noise.wav');
%[noise,fs1,bits1]=wavread('F:\语音降噪\wav\pc_noise.wav');
y=mixsig(y1,noise,20);% 混合
y=y/max(abs(y));%归一化
wavwrite(y,8000,8,'F:\noise enhancing\wav\mymasking_s&w(20).wav');
figure(2);
plot(y);

frame = 256;    % Defining frame size
shift=128;
win=hamming(256);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

ps_noise=zeros(length(signal)/frame,frame);
frame_temp = zeros(length(signal)/frame,frame);

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);
    
    
%%%%%% START OF THE NOISE ELIMINATION THROUGH SPECTRAL SUBTRACTION BASED ON THE THRESHOLD SET %%%%%%

   for k = 1 :( length(signal)/shift-1),
        for m = 1 : frame,
          abc1(m) = signal(head+m);
          
        end;
        %abc1=abc1.*win';
        
        head = head +shift;
        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