seance1.m

A partir d un son, permet de reperer les tonales selon en utilisant l echelle de Bark

clc
close all
clear all

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%% Sensibilisation with voice signal and hearing pattern properties%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Absolute Hearing Threshold %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

figure(1)
f=[0.02:0.01:20];
semilogx(f,Sa_(f));
% Ploting in semilog scale in order to have the same figure as the subject
xlabel('Frequency ');
ylabel('Decibel Sound Pressure Level (dB SPL)');
title('Absolute Hearing Edge');


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Listening of the loading sound %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

fid = fopen('waziwaza.raw'); %fid negative mean the file couldn't be open
wave = fread(fid,'short');
soundsc(wave,16000); 

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Plotting of a temporal wave %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

figure(2)
t=[1/16000:1/16000:8550*2/16000];
plot(t,wave)
xlim([0 0.55]);
xlabel('time in second');
ylabel('amplitude of the wave');
title('temporal wave of waziwaza sound');



%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Disturbance and hearing of the noised signal %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

figure(3)
N=17100;
t=[1/16000:1/16000:N/16000];
sigma2=5*10^10;
noise = sqrt(sigma2)*randn(N,1); %Gaussian Centred White Noise with sigma2's variance
wave_noised = wave + noise; % noised wave
subplot 311
plot(t,noise)    
xlim([0 0.55]);
xlabel('time in second');
ylabel('GCWN');
title('Gaussian Centred White Noise with sigma2''s variance');

subplot 312
plot(t,wave)
xlim([0 0.55]);
xlabel('time in second');
ylabel('wave amplitude');
title('Temporal signal of waziwaza sound');

subplot 313
plot(t,wave_noised)
xlim([0 0.55]);
ylim([-1*10^9 2*10^9]);
xlabel('time in second');
ylabel('Disturbed wave amplitude');
title('Temporal signal of waziwaza sound disturbed with a GCW Noised');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Visualisation de la r閜onse fr閝uentielle du filtre %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

b=[0.29,0.92,1.30,0.92,0.29];
a=[1,1.57,0.72,0.26,0.17];



[H,F] = freqz(b,a);

figure(5)
subplot 211
plot(F*16000/(2*pi),abs(H)); %amplitude
xlabel('f');
ylabel('amplitude |H(f)|');
title('Filter Frequency Response');

subplot 212
plot(F*16000/(2*pi),unwrap(angle(H))); %phase
xlabel('f');
ylabel('phase arg(H(f))');

figure(22)
zplane(b,a)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Filtrage du signal d'origine %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


y = filter(b,a,wave);
figure(6)
subplot 211
t=[1/16000:1/16000:8550*2/16000];
plot(t,wave)
xlim([0 0.55]);
xlabel('Time in second');
ylabel('Magnitude of the wave');
title('Temporal wave of waziwaza sound');

subplot 212
plot(t,y);
xlim([0 0.55]);
xlabel('Time in second');
ylabel(' Magnitude ');
title('Filtered Signal');