Reduction of broadband noise in speech signals by multilinear subspace analysis

Yusuke Sato, Tetsuya Hoya, Hovagim Bakardjian, Andrzej Cichocki

Research output: Contribution to conferencePaperpeer-review

Abstract

A new noise reduction method for speech signals is proposed in this paper. The method is based upon the N-mode singular value decomposition algorithm, which exploits the multilinear subspace analysis of given speech data. Simulation results using both synthetically generated and real broadband noise components show that the enhancement quality obtained by the multilinear subspace analysis method in terms of both segmental gain and cepstral distance, as well as informal listening tests, is superior to that by a conventional nonlinear spectral subtraction method and the previously proposed approach based upon sliding subspace projection.

Original languageEnglish
Pages965-968
Number of pages4
Publication statusPublished - 2010
Externally publishedYes
Event11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010 - Makuhari, Chiba, Japan
Duration: 26 Sep 201030 Sep 2010

Conference

Conference11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010
Country/TerritoryJapan
CityMakuhari, Chiba
Period26/09/1030/09/10

Keywords

  • Broadband noise reduction
  • Multilinear subspace analysis
  • Speech enhancement

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