Designing multichannel source separation based on single-channel source separation

Ana Ramirez Lopez, Nobutaka Ono, Ulpu Remes, Kalle Palomäki, Mikko Kurimo

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

9 Citations (Scopus)

Abstract

In this paper, an extension of independent vector analysis (IVA), model-based IVA, is proposed for multichannel source separation. For obtaining better source models, we introduce a single-channel source separation method, and utilize the outputs as source variances in time-frequency-variant Gaussian source model. The demixing matrices are estimated in the same way as a state-of-the-art IVA method, auxiliary-function-based IVA (AuxIVA). Experimental evaluations show that the proposed approach is effective and improves the source separation performance of IVA. In addition, several post-filters aiming to realize multichannel Wiener filter (MWF) are investigated. This setup proves to further increase the performance of IVA. The presented method shows a potential to provide a general way to improve the separation performance from single-channel source separation to multichannel source separation.
Original languageEnglish
Title of host publicationIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, April 19-24, 2015
Place of Publicationunknown
PublisherIEEE
Pages469-473
ISBN (Print)978-1-4673-6997-8
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication

Publication series

NameInternational Conference on Acoustics Speech and Signal Processing ICASSP
ISSN (Print)1520-6149

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