Title: | Discriminative Layered Nonnegative Matrix Factorization for Speech Separation |
Authors: | Hsu, Chung-Chien Chi, Tai-Shih Chien, Jen-Tzung 電機工程學系 Department of Electrical and Computer Engineering |
Keywords: | dictionary learning;discriminative learning;nonnegative matrix factorization;speech separation |
Issue Date: | 1-Jan-2016 |
Abstract: | This paper proposes a discriminative layered nonnegative matrix factorization (DL-NMF) for monaural speech separation. The standard NMF conducts the parts-based representation using a single-layer of bases which was recently upgraded to the layered NMF (L-NMF) where a tree of bases was estimated for multi-level or multi-aspect decomposition of a complex mixed signal. In this study, we develop the DL-NMF by extending the generative bases in L-NMF to the discriminative bases which are estimated according to a discriminative criterion. The discriminative criterion is conducted by optimizing the recovery of the mixed spectra from the separated spectra and minimizing the reconstruction errors between separated spectra and original source spectra. The experiments on single-channel speech separation show the superiority of DL-NMF to NMF and L-NMF in terms of the SDR, SIR and SAR measures. |
URI: | http://dx.doi.org/10.21437/Interspeech.2016-415 http://hdl.handle.net/11536/146771 |
ISSN: | 2308-457X |
DOI: | 10.21437/Interspeech.2016-415 |
Journal: | 17TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2016), VOLS 1-5: UNDERSTANDING SPEECH PROCESSING IN HUMANS AND MACHINES |
Begin Page: | 560 |
End Page: | 564 |
Appears in Collections: | Conferences Paper |