Speech enhancement by online non-negative spectrogram decomposition in non-stationary noise environments

Zhiyao Duan, Gautham J. Mysore, Paris Smaragdis

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

Abstract

Classical single-channel speech enhancement algorithms have two convenient properties: they require pre-learning the noise model but not the speech model, and they work online. However, they often have difficulties in dealing with non-stationary noise sources. Source separation algorithms based on nonnegative spectrogram decompositions are capable of dealing with non-stationary noise, but do not possess the aforementioned properties. In this paper we present a novel algorithm that combines the advantages of both classical algorithms and non-negative spectrogram decomposition algorithms. Experiments show that it significantly outperforms four categories of classical algorithms in non-stationary noise environments.

Original languageEnglish (US)
Title of host publication13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
Pages594-597
Number of pages4
StatePublished - Dec 1 2012
Event13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012 - Portland, OR, United States
Duration: Sep 9 2012Sep 13 2012

Publication series

Name13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
Volume1

Other

Other13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
Country/TerritoryUnited States
CityPortland, OR
Period9/9/129/13/12

Keywords

  • Nonnegative matrix factorization
  • Online algorithm
  • Source separation
  • Speech enhancement

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Communication

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