Post-processing for convolutive blind source separation

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Aichner R, Zourub M, Buchner H, Kellermann W
Publication year: 2006
Volume: 5
ISBN: 9781424404698
ISSN: 15206149
Language: English


Abstract


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 crosstalk 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. © 2006 IEEE.


FAU Authors / FAU Editors

Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik


How to cite

APA:
Aichner, R., Zourub, M., Buchner, H., & Kellermann, W. (2006). Post-processing for convolutive blind source separation. In Proceedings of the 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006. Toulouse, FR.

MLA:
Aichner, Robert, et al. "Post-processing for convolutive blind source separation." Proceedings of the 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, Toulouse 2006.

BibTeX: 

Last updated on 2019-31-05 at 18:38