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Why is the speech signal not convolutional mixing in main. m
Hello, d-kitamura, thanks for your amazing work!
I have just started exploring BSS and I have a question. Why is the signal not convolutional mixing in main. m? The reason why I raised this question is because I used RIR simulation to convolve mixed speech signals, but the performance of IVA was very poor. I want to know why the performance is so poor. Can you provide some suggestions?
following is the matlab code:
roomDimensions = [7 5 2.75];
microLocation = [3 1 1.5; 3.5 1 1.5; 4 1 1.5];
sourceLocation = [2 3.5 1.5; 4 3.5 1.5; 6 3.5 1.5];
c = 343; % Sound velocity (m/s)
fs = 44100; % Sample frequency (samples/s)
beta = 0; % Reverberation time (s)
n = 4096; % Number of samples
mtype = 'omnidirectional'; % Type of microphone
order = -1; % -1 equals maximum reflection order!
dim = 3; % Room dimension
orientation = 0; % Microphone orientation (rad)
hp_filter = 1; % Enable high-pass filter
h = rir_generator(c, fs, microLocation, sourceLocation, roomDimensions, beta, n, mtype, order, dim, orientation, hp_filter);
mixSig(:,1) = conv(srcSig(:,1),h(1,:), 'same') + conv(srcSig(:,2),h(1,:), 'same') + conv(srcSig(:,3),h(1,:), 'same');
mixSig(:,2) = conv(srcSig(:,1),h(2,:), 'same') + conv(srcSig(:,2),h(2,:), 'same') + conv(srcSig(:,3),h(2,:), 'same');
mixSig(:,3) = conv(srcSig(:,1),h(3,:), 'same') + conv(srcSig(:,2),h(3,:), 'same') + conv(srcSig(:,3),h(3,:), 'same');
%% using AuxIVA
% Set parameters
seed = 1; % pseudo random seed
refMic = 1; % reference microphone for back projection
nSrc = 3; % number of sources
fftSize = 4096; % window length in STFT [points]
shiftSize = 2048; % shift length in STFT [points]
windowType = "hamming"; % window function used in STFT
nIter = 30; % number of iterations (define by checking convergence behavior with drawConv=true)
applyWhitening = false; % true or false (true: apply whitening to the observed multichannel spectrograms)
drawConv = true; % true or false (true: plot cost function values in each iteration and show convergence behavior, false: faster and do not plot cost function values)
% Fix random seed
RandStream.setGlobalStream(RandStream('mt19937ar','Seed',seed))
% Blind source separation based on AuxIVA-ISS
[estSig_auxiva, cost] = AuxIVAISS(mixSig, nSrc, targetFs, fftSize, shiftSize, windowType, nIter, refMic, applyWhitening, drawConv);
implicit expansion on matlab script
hi, kitamura,
Thanks for your sharing on BSS scripts which help me a lot on understanding BSS algorithms.
Here is a question.
There are many implicit expansions at matlab script, where I counter error when running it at Matlab R2013a.
for example, in AuxIVAISS.m
YY = Y .* conj(Y(n,:,:)); % N x J x I, using implicit expansion (NxJxI .* 1xJxI)
- do you use other version of Matlab, so you can run the scripts without error?
- I'm not sure what this multiplication with expansion really mean?
Can it be used to separate music?
Hello, thank you very much for sharing. I saw that there are two music signals in your input folder. As far as I know, its objective function is based on speech statistical models such as Laplacian distribution. So, is it applicable to music signals ?
How to change AuxIVA-ISS to online version
Hi d-kitamura,
The AuxIVA-ISS you provided is very helpful. When I tried to make this program into an online version, I found it couldn’t converge, it is no problem with AuxIVA-IP. Is this related to the update method?
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