Aichner R, Zourub M, Buchner H, Kellermann W (2006)
Publication Language: English
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2006
Book Volume: 5
Article Number: 1661206
ISBN: 9781424404698
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33947628312∨igin=inward
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.
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: Download