Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
On relational data versions of c-means algorithms
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Online blind source separation based on time-frequency sparseness
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Fast approximate joint diagonalization incorporating weight matrices
IEEE Transactions on Signal Processing
The 2010 signal separation evaluation campaign (SiSEC2010): audio source separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
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We present an adaptive algorithm for blind audio source separation (BASS) of moving sources via Independent Component Analysis (ICA) in time-domain. The method is shown to achieve good separation quality even with a short demixing filter length (L = 30). Our experiments show that the proposed adaptive algorithm can outperform the off-line version of the method (in terms of the average output SIR), even in the case in which the sources do not move, because it is capable of better adaptation to the nonstationarity of the speech.