Effacer les filtres
Effacer les filtres

how to remove noise from audio using fourier transform and filter and to obtain back the original audio signal

11 vues (au cours des 30 derniers jours)
[y,Fs]=audioread('audio.wav');
%Normal sound
sound(y,Fs);
subplot(3,1,1);
plot(y);
x=y(1:2:length(y));%x=y(1:2:end)
%Decimated sound
sound(x,Fs);
subplot(3,1,2);
plot(x);
xn=randn(384362,1);
yn=y+xn;
sound(yn,Fs);
x1(1)=y(1);
g=length(y)-1;
j=2;
i=2;
while g~=0
m=rem(i,2);
if m==0
x1(i)=0;
else
x1(i)=y(j);
j=j+1;
g=g-1;
end
i=i+1;
end
%Interpolated sound
sound(x1,Fs);
subplot(3,1,3);
plot(x1);
srate = 10000;
time = 0:1/srate:2;
npnts = length(time);
% signal
signal = y;
% Fourier spectrum
signalX = fft(signal);
hz = linspace(0,srate/2,npnts);
% amplitude
ampl = abs(signalX(1:length(hz)));
figure(1);
stem(signal);
figure(2), clf
stem(hz,ampl,'ks-','linew',3,'markersize',10,'markerfacecolor','w')
% make plot look a bit nicer
set(gca,'xlim',[0 10])
xlabel('Frequency (Hz)'), ylabel('Amplitude (a.u.)')

Réponses (1)

Suhan
Suhan le 22 Fév 2018
Hi,
The following documentation demonstrates discarding noise from the data using 'fft': https://in.mathworks.com/help/matlab/math/fourier-transforms.html
Once you discard the noise spectrum, you can use 'ifft' to recover the signal. For 'ifft' refer to the following: https://in.mathworks.com/help/matlab/ref/ifft.html

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