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Post-Processing for Convolutive Blind Source Separation

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4 Author(s)
Aichner, R. ; Multimedia Commun. & Signal Process., Erlangen-Nurnberg Univ., Erlangen ; Zourub, M. ; Buchner, H. ; Kellermann, W.

Convolutive blind source separation (BSS) aims at separating point sources from mixtures picked up by several sensors. In real-world environments moving speakers, background noise and long reverberation are encountered which often degrade the performance of BSS algorithms. In such cases, the application of a post-filter can improve the output signal quality by suppression of residual cross-talk and of background noise. In this paper we propose a novel technique to estimate the necessary power spectral densities of the cross-talk components and present a robust system which allows to further suppress both, the remaining interference from point sources and the background noise. Experimental results show the benefit of this post-processing method in realistic environments

Published in:

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on  (Volume:5 )

Date of Conference:

14-19 May 2006