Discriminative layered nonnegative matrix factorization for speech separation

Chung Chien Hsu, Tai-Shih Chi, Jen-Tzung Chien

研究成果: Conference article同行評審

3 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)560-564
頁數5
期刊Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
08-12-September-2016
DOIs
出版狀態Published - 1 一月 2016
事件17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016 - San Francisco, United States
持續時間: 8 九月 201616 九月 2016

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