Started code for DSP final project

2024-04-25 18:38:09 -04:00
parent 824a46b1fd
commit 50a5e57e18
96 changed files with 2160495 additions and 28 deletions
--- a/6th-Semester-Spring-2024/DSP/Labs/FinalProject/statistical_based/stsa_wcosh.m
+++ b/6th-Semester-Spring-2024/DSP/Labs/FinalProject/statistical_based/stsa_wcosh.m
@@ -0,0 +1,131 @@
+function stsa_wcosh(filename,outfile,p)
+
+%
+%  Implements the Bayesian estimator based on the weighted cosh
+%  distortion measure [1, Eq. 34].
+% 
+%  Usage:  stsa_wcosh(noisyFile, outputFile, p)
+%           
+%         infile - noisy speech file in .wav format
+%         outputFile - enhanced output file in .wav format
+%         p  - power exponent used in the weighted cosh measure.
+%              Valid values for p: p>-1
+%  
+%
+%  Example call:  stsa_wcosh('sp04_babble_sn10.wav','out_wcosh.wav',-0.5);
+%
+%  References:
+%   [1] Loizou, P. (2005). Speech enhancement based on perceptually motivated 
+%       Bayesian estimators of the speech magnitude spectrum. IEEE Trans. on Speech 
+%       and Audio Processing, 13(5), 857-869.
+%   
+% Author: Philipos C. Loizou
+%
+% Copyright (c) 2006 by Philipos C. Loizou
+% $Revision: 0.0 $  $Date: 10/09/2006 $
+%-------------------------------------------------------------------------
+
+if nargin<3
+    fprintf('Usage: stsa_wcosh(infile.wav,outfile.wav,p) \n');
+    fprintf('       where p>-1 \n\n');
+    return;
+end;
+
+if p<-1
+    error('ERROR!  p needs to be larger than -1.\n\n');
+end
+
+[x, Srate, bits]= wavread( filename);	
+
+
+
+% =============== Initialize variables ===============
+%
+
+len=floor(20*Srate/1000); % Frame size in samples
+if rem(len,2)==1, len=len+1; end;
+PERC=50; % window overlap in percent of frame size
+len1=floor(len*PERC/100);
+len2=len-len1; 
+
+
+win=hanning(len); %tukey(len,PERC);  % define window
+
+
+
+% Noise magnitude calculations - assuming that the first 6 frames is noise/silence
+%
+nFFT=2*len;
+nFFT2=len/2;
+noise_mean=zeros(nFFT,1);
+j=1;
+for k=1:5
+   noise_mean=noise_mean+abs(fft(win.*x(j:j+len-1),nFFT));
+   j=j+len;
+end
+noise_mu=noise_mean/5;
+noise_mu2=noise_mu.^2;
+
+%--- allocate memory and initialize various variables
+   
+x_old=zeros(len1,1);
+Nframes=floor(length(x)/len2)-1;
+xfinal=zeros(Nframes*len2,1);
+
+
+%===============================  Start Processing =======================================================
+%
+k=1;
+aa=0.98;
+CC2=sqrt(gamma((p+3)/2)/gamma((p+1)/2));
+
+for n=1:Nframes 
+   
+  
+   insign=win.*x(k:k+len-1);
+    
+   %--- Take fourier transform of  frame
+   
+   spec=fft(insign,nFFT);   
+   sig=abs(spec); % compute the magnitude
+   sig2=sig.^2;
+   
+       gammak=min(sig2./noise_mu2,40);  % post SNR
+       if n==1
+           ksi=aa+(1-aa)*max(gammak-1,0);
+       else
+       
+           ksi=aa*Xk_prev./noise_mu2 + (1-aa)*max(gammak-1,0);     % a priori SNR   
+          
+       end
+     
+       vk=ksi.*gammak./(1+ksi);
+       
+         
+       % --- for the weighted cosh measure
+       
+       numer=CC2*sqrt(vk.*confhyperg(-(p+1)/2,1,-vk,100));
+       denom=gammak.*sqrt(confhyperg(-(p-1)/2,1,-vk,100));
+       hw=numer./denom;
+       
+       
+       sig=sig.*hw;
+       Xk_prev=sig.^2;
+       
+       xi_w= ifft( hw .* spec, nFFT); 
+	   xi_w= real( xi_w);
+	
+          
+	% --- Overlap and add ---------------
+    %
+    xfinal(k:k+ len2-1)= x_old+ xi_w(1:len1);
+	x_old= xi_w(len1+ 1: len);
+   
+ 
+ k=k+len2;
+end
+%========================================================================================
+
+
+wavwrite(xfinal,Srate,16,outfile);
+