Discriminative non-negative matrix factorization with majorization-minimization

Li Li, Hirokazu Kameoka, Shoji Makino

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Non-negative matrix factorization (NMF) is a powerful approach to single channel audio source separation. In a supervised setting, NMF is first applied to train the basis spectra of each sound source. At test time, NMF is applied to the spectrogram of a mixture signal using the pretrained spectra. The source signals can then be separated out using a Wiener filter. A typical way to train the basis spectra of each source is to minimize the objective function of NMF. However, the basis spectra obtained in this way do not ensure that the separated signal will be optimal at test time due to the inconsistency between the objective functions for training and separation (Wiener filtering). To address this, a framework called discriminative NMF (DNMF) has recently been proposed. In in this work a multiplicative update algorithm was proposed for the basis training, however one drawback is that the convergence is not guaranteed. To overcome this drawback, this paper proposes using a majorization-minimization principle to develop a convergence-guaranteed algorithm for DNMF. Experimental results showed that the proposed algorithm outperformed standard NMF and DNMF using a multiplicative update algorithm as regards both the signal-to-distortion and signal-to-interference ratios.

Original languageEnglish
Title of host publication2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages141-145
Number of pages5
ISBN (Electronic)9781509059256
DOIs
Publication statusPublished - 2017 Apr 10
Externally publishedYes
Event2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - San Francisco, United States
Duration: 2017 Mar 12017 Mar 3

Publication series

Name2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings

Conference

Conference2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017
Country/TerritoryUnited States
CitySan Francisco
Period17/3/117/3/3

Keywords

  • Discriminative non-negative matrix factorization
  • Majorization-minimization
  • Single channel
  • Speech enhancement

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Acoustics and Ultrasonics
  • Instrumentation
  • Communication

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