Mentoring-reverse mentoring for unsupervised multi-channel speech source separation

Yu Nakagome, Masahito Togami, Tetsuji Ogawa, Tetsunori Kobayashi

Research output: Contribution to journalConference articlepeer-review

Abstract

Mentoring-reverse mentoring, which is a novel knowledge transfer framework for unsupervised learning, is introduced in multi-channel speech source separation. This framework aims to improve two different systems, which are referred to as a senior and a junior system, by mentoring each other. The senior system, which is composed of a neural separator and a statistical blind source separation (BSS) model, generates a pseudo-target signal. The junior system, which is composed of a neural separator and a post-filter, was constructed using teacher-student learning with the pseudo-target signal generated from the senior system i.e, imitating the output from the senior system (mentoring step). Then, the senior system can be improved by propagating the shared neural separator of the grown-up junior system to the senior system (reverse mentoring step). Since the improved neural separator can give better initial parameters for the statistical BSS model, the senior system can yield more accurate pseudo-target signals, leading to iterative improvement of the pseudo-target signal generator and the neural separator. Experimental comparisons conducted under the condition where mixture-clean parallel data are not available demonstrated that the proposed mentoring-reverse mentoring framework yielded improvements in speech source separation over the existing unsupervised source separation methods.

Original languageEnglish
Pages (from-to)86-90
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2020-October
DOIs
Publication statusPublished - 2020
Event21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020 - Shanghai, China
Duration: 2020 Oct 252020 Oct 29

Keywords

  • Deep neural network
  • Mentoring-reverse mentoring
  • Speech source separation
  • Unsupervised training

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modelling and Simulation

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