www.pudn.com > VQmatlab.rar > demo.m

17 / 18 
% Demo script that generates all graphics in the report 
% and demonstrates our results. 
% 
% 
%%%%%%%%%%%%%%%%%% 
% Mini-Project: An automatic speaker recognition system 
% 
% Responsible: Vladan Velisavljevic 
% Authors: Christian Cornaz 
% Urs Hunkeler 
disp('Mini-Projet: Automatic Speaker Recognition'); 
disp('By Christian Cornaz & Urs Hunkeler (SC)'); 
disp('Responsible Assistant: Vladan Velisavljevic'); 
disp(' '); 
disp(' '); 
[s1 fs1] = wavread('train\s1.wav'); 
[s2 fs2] = wavread('train\s2.wav'); 
%Question 2 
disp('> Question 2'); 
t = 0:1/fs1:(length(s1) - 1)/fs1; 
plot(t, s1), axis([0, (length(s1) - 1)/fs1 -0.4 0.5]); 
title('Plot of signal s1.wav'); 
xlabel('Time [s]'); 
ylabel('Amplitude (normalized)') 
pause 
close all 
%Question 3 (linear) 
disp('> Question 3: linear spectrum plot'); 
M = 100; 
N = 256; 
frames = blockFrames(s1, fs1, M, N); 
t = N / 2; 
tm = length(s1) / fs1; 
subplot(121); 
imagesc([0 tm], [0 fs1/2], abs(frames(1:t, :)).^2), axis xy; 
title('Power Spectrum (M = 100, N = 256)'); 
xlabel('Time [s]'); 
ylabel('Frequency [Hz]'); 
colorbar; 
%Question 3 (logarithmic) 
disp('> Question 3: logarithmic spectrum plot'); 
subplot(122); 
imagesc([0 tm], [0 fs1/2], 20 * log10(abs(frames(1:t, :)).^2)), axis xy; 
title('Logarithmic Power Spectrum (M = 100, N = 256)'); 
xlabel('Time [s]'); 
ylabel('Frequency [Hz]'); 
colorbar; 
D=get(gcf,'Position'); 
set(gcf,'Position',round([D(1)*.5 D(2)*.5 D(3)*2 D(4)*1.3])) 
pause 
close all 
%Question 4 
disp('> Question 4: Plots for different values for N'); 
lN = [128 256 512]; 
u=220; 
for i = 1:length(lN) 
N = lN(i); 
M = round(N / 3); 
frames = blockFrames(s1, fs1, M, N); 
t = N / 2; 
temp = size(frames); 
nbframes = temp(2); 
u=u+1; 
subplot(u) 
imagesc([0 tm], [0 fs1/2], 20 * log10(abs(frames(1:t, :)).^2)), axis xy; 
%Mini-Project: An automatic speaker recognition system 
%Christian Cornaz, Urs Hunkeler 03.02.2003 
title(sprintf('Power Spectrum (M = %i, N = %i, frames = %i)', M, N, nbframes)); 
xlabel('Time [s]'); 
ylabel('Frequency [Hz]'); 
colorbar 
end 
D=get(gcf,'Position'); 
set(gcf,'Position',round([D(1)*.5 D(2)*.5 D(3)*1.5 D(4)*1.5])) 
pause 
close all 
%Question 5 
disp('> Question 5: Mel Space'); 
plot(linspace(0, (fs1/2), 129), (melfb(20, 256, fs1))'); 
title('Mel-Spaced Filterbank'); 
xlabel('Frequency [Hz]'); 
pause 
close all 
%Question 6 
disp('> Question 6: Modified spectrum'); 
M = 100; 
N = 256; 
frames = blockFrames(s1, fs1, M, N); 
n2 = 1 + floor(N / 2); 
m = melfb(20, N, fs1); 
z = m * abs(frames(1:n2, :)).^2; 
t = N / 2; 
tm = length(s1) / fs1; 
subplot(121) 
imagesc([0 tm], [0 fs1/2], abs(frames(1:n2, :)).^2), axis xy; 
title('Power Spectrum unmodified'); 
xlabel('Time [s]'); 
ylabel('Frequency [Hz]'); 
colorbar; 
subplot(122) 
imagesc([0 tm], [0 20], z), axis xy; 
title('Power Spectrum modified through Mel Cepstrum filter'); 
xlabel('Time [s]'); 
ylabel('Number of Filter in Filter Bank'); 
colorbar; 
D=get(gcf,'Position'); 
set(gcf,'Position',[0 D(2) D(3)*2 D(4)]) 
pause 
close all 
%Question 7 
disp('> Question 7: 2D plot of accustic vectors'); 
c1 = mfcc(s1, fs1); 
c2 = mfcc(s2, fs2); 
plot(c1(5, :), c1(6, :), 'or'); 
hold on; 
plot(c2(5, :), c2(6, :), 'xb'); 
xlabel('5th Dimension'); 
ylabel('6th Dimension'); 
legend('Signal 1', 'Signal 2'); 
title('2D plot of accoustic vectors'); 
pause 
close all 
%Question 8 
disp('> Question 8: Plot of the 2D trained VQ codewords') 
d1 = vqlbg(c1,16); 
d2 = vqlbg(c2,16); 
plot(c1(5, :), c1(6, :), 'xr') 
hold on 
plot(d1(5, :), d1(6, :), 'vk') 
plot(c2(5, :), c2(6, :), 'xb') 
plot(d2(5, :), d2(6, :), '+k') 
xlabel('5th Dimension'); 
ylabel('6th Dimension'); 
legend('Speaker 1', 'Codebook 1', 'Speaker 2', 'Codebook 2'); 
title('2D plot of accoustic vectors'); 
pause 
close all