A frequency domain method for blind source separation of convolutive audio mixtures

In this paper, we propose a new frequency domain approach to blind source separation (BSS) of audio signals mixed in a reverberant environment. We propose a joint diagonalization procedure on the cross power spectral density matrices of the signals at the output of the mixing system to identify the...

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Bibliographic Details
Published in:IEEE transactions on speech and audio processing 2005-09, Vol.13 (5), p.832-844
Main Authors: Rahbar, K., Reilly, J.P.
Format: Article
Language:English
Subjects:
Algorithms
Ambiguity
Audio enhancement
Blind source separation
Blinds
Convergence
Density
Frequency dependence
Frequency domain analysis
frequency domain blind source separation
Frequency domains
Frequency estimation
joint diagonalization
Optimization methods
permutation ambiguity
Permutations
Separation
Signal processing
Signal processing algorithms
Source separation
Spectra
Studies
Time domain analysis
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Summary:In this paper, we propose a new frequency domain approach to blind source separation (BSS) of audio signals mixed in a reverberant environment. We propose a joint diagonalization procedure on the cross power spectral density matrices of the signals at the output of the mixing system to identify the mixing system at each frequency bin up to a scale and permutation ambiguity. The frequency domain joint diagonalization is performed using a new and quickly converging algorithm which uses an alternating least-squares (ALS) optimization method. The inverse of the mixing system is then used to separate the sources. An efficient dyadic algorithm to resolve the frequency dependent permutation ambiguities that exploits the inherent nonstationarity of the sources is presented. The effect of the unknown scaling ambiguities is partially resolved using an initialization procedure for the ALS algorithm. The performance of the proposed algorithm is demonstrated by experiments conducted in real reverberant rooms. Performance comparisons are made with previous methods.
ISSN:1063-6676
2329-9290
1558-2353
2329-9304
DOI:10.1109/TSA.2005.851925