Abstract
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.
This work was partly supported by Ministry of Education, Youth and Sports of the Czech Republic through the project 1M0572 and partly by Grant Agency of the Czech Republic through the projects 102/09/1278 and 102/08/0707.
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Málek, J., Koldovský, Z., Tichavský, P. (2010). Adaptive Time-Domain Blind Separation of Speech Signals. In: Vigneron, V., Zarzoso, V., Moreau, E., Gribonval, R., Vincent, E. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2010. Lecture Notes in Computer Science, vol 6365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15995-4_2
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DOI: https://doi.org/10.1007/978-3-642-15995-4_2
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