10-04-2017, 07:49 PM
speech separation matlab code
% NAME
% spSeparationCepstrum - Source-Filter Separation via Cepstrum
% SYNOPSIS
% [source, filter, c, y] =
% spSeparationCepstrum(x, fs, ncoef, window, show)
% DESCRIPTION
% Source-Filter Separation via the Cepstrum.
% This deconvolve speech signal into source (vocal codes, white noise)
% and filter (oral cavity, coloring, envelope) component
% INPUTS
% x (vector) of size Nx1 which contains one frame signal
% fs (scalar) the sampling rate
% [ncoef]
% (scalar) the number of coefficients of cepstrum to treat
% as low-time parts. The default uses
% ncoef = 2 + fs / 1000;
% as a rule of thumb.
% [window]
% (string) the window function such as 'rectwin', 'hamming'.
% The default is 'rectwin' (or no window).
% [show] (boolean) plot or not. The default is 0.
% OUTPUTS
% source (vector) of size Nx1 which containts log magnitude (not dB)
% frequency response of high-time cepstrum parts that is
% source (vocal tract, white noise) component
% filter (vector) of size Nx1 which constains log magnitude (not dB)
% frequency response of low-time cepstrum parts that is
% filter (oral cavity, coloring, envelope) component
% [c] (vector) of size Nx1 which contains cepstrum coefficients
% [y] (vector) of size Nx1 which contains frequency response of input
% AUTHOR
% Naotoshi Seo, April 2008
function [source, filter, c, y] = spSeparationCepstrum(x, fs, ncoef, window, show)
%% initialization
N = length(x);
x = x(
;if exist('show', 'var') isempty(show)
show = 0;
end
if exist('window', 'var') isempty(window)
window = 'rectwin';
end
if exist('ncoef', 'var') isempty(ncoef)
ncoef = 2 + round(fs / 1000);
end
%% get cepstrum
[c, y] = spCepstrum(x, window);
%% get high-time spectrum response
highc = [zeros(ncoef,1); c(ncoef:end)];
source = fft(highc); % recover high-time parts to log mag freq response
%% get low-time spectrum response
lowc = [c(1:ncoef); zeros(length©-ncoef,1)];
filter = fft(lowc); % recover low-time parts to log mag freq response
%% plot
if show
figure;
ms1=fs/1000; % 1ms. maximum speech Fx at 1000Hz
ms20=fs/50; % 20ms. minimum speech Fx at 50Hz
% plot waveform
t=(0:N-1)/fs; % times of sampling instants
subplot(3,2,1);
plot(t,x);
xlabel('Time (s)');
ylabel('Amplitude');
title('(a) Waveform');
% plot log spectrum
f = (0:N/2-1)*fs/N; % rest half is mirror for real signal
db = 20*log(abs(y(1:length(f));
subplot(3,2,2);
plot(f,db);
title('(b) Spectrum');
xlabel('Frequency (Hz)');
ylabel('Magnitude (dB)');
ylim([-100 100]);
% plot cepstrum between 1ms (=1000Hz) and 20ms (=50Hz)
q=(ms1:ms20)/fs;
subplot(3,2,3);
plot(q,abs(c(ms1:ms20));
title('© Cepstrum');
xlabel('Quefrency (s)');
ylabel('Amplitude');
% plot low-time spectrum response
subplot(3,2,4);
plot(f,20*real(filter(1:length(f));
title('(d) Low-time Spectrum (Filter)');
xlabel('Frequency (Hz)');
ylabel('Magnitude (dB)');
ylim([-100 100]);
% plot high-time spectrum response
subplot(3,2,6);
plot(f,20*real(source(1:length(f));
title('(e) High-time Spectrum (Source)');
xlabel('Frequency (Hz)');
ylabel('Magnitude (dB)');
ylim([-100 100]);
end
end
function spSeparationCepstrumDemo
x1 = wgn(1000, 1, 1); fs = 16000;
c = spSeparationCepstrum(x1, fs, 20, 'hamming', 'plot');
[x2, fs] = wavread('bee.wav'); x2 = x2(1001:2000);
c = spSeparationCepstrum(x2, fs, 20, 'hamming', 'plot');
x3 = awgn(x2,50);
c = spSeparationCepstrum(x3, fs, 20, 'hamming', 'plot');
end