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开源软件名称(OpenSource Name):mim/messl开源软件地址(OpenSource Url):https://github.com/mim/messl开源编程语言(OpenSource Language):MATLAB 98.1%开源软件介绍(OpenSource Introduction):Model-Based EM Source Separation and LocalizationCopyright 2006-2009 Michael I Mandel and Ron Weiss, all rights reserved [email protected] and [email protected] Last updated 2009-08-20 Basic usage to separate two sources:addpath('./plottools/')
% % Load stereo wav files of the same length and mix them
% [y1 fs] = wavread('data/src1.wav');
% [y2 fs] = wavread('data/src2.wav');
% lr = y1' + y2';
% Load pre-mixed version of those two files (don't forget the transpose)
[lr fs] = wavread('data/mix.wav');
lr = lr';
% Derive grid of tau values (use your numbers here)
tau = tauGrid(0.15, fs, 31);
% Run MESSL
[m,p] = messl(lr, tau, 2, 'vis', 1);
% Reconstruct wavforms from masks
yhat1 = reconstruct(m, lr, 1);
yhat2 = reconstruct(m, lr, 2); Fancier usageInitialized from PHAT-histogram: % Localize and then run MESSL
tdoa = phatLoc(lr, tau, 2, 1024, 1);
[m,p] = messl(lr, tau, 2, 'vis', 1, 'tauPosInit', tdoa); Even fancier usage, garbage source and ILD prior (better in reverb, but only when using dummy-head recordings): [m,p] = messl(lr, tau, 2, 'vis', 1, 'ildPriorPrec', 3, ...
'GarbageSrc', 1, 'sr', 16000); Can also use prob2mask to make the mask more definitive, i.e. closer to binary, but not binary. m2 = prob2mask(m);
yhat1 = reconstruct(m2, lr, 1);
yhat2 = reconstruct(m2, lr, 2); |
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