Discriminative noise adaptive training approach for an environment migration

Byung Ok Kang, Ho Young Jung, Yun Keun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A combined strategy of noise-adaptive training (NAT) and discriminative-based adaptation is proposed for effective migration of speech recognition systems to other noisy environments. NAT is an effective approach for real-field applications, but does not satisfy the minimum classification error (MCE) criterion for the recognition process and adapts poorly to new environments. The proposed method makes up for the weak points in discriminative adaptation strategies, and presents a new method for improving the MCE approach. Using this new method, experimental results show that the speech recognition system can successfully be migrated to other environments using specific-condition data of the target environment.

Original languageEnglish
Title of host publicationInternational Speech Communication Association - 8th Annual Conference of the International Speech Communication Association, Interspeech 2007
PublisherUnavailable
Pages1329-1332
Number of pages4
ISBN (Print)9781605603162
StatePublished - 2007
Event8th Annual Conference of the International Speech Communication Association, Interspeech 2007 - Antwerp, Belgium
Duration: 27 Aug 200731 Aug 2007

Publication series

NameInternational Speech Communication Association - 8th Annual Conference of the International Speech Communication Association, Interspeech 2007
Volume2
ISSN (Electronic)1990-9772

Conference

Conference8th Annual Conference of the International Speech Communication Association, Interspeech 2007
Country/TerritoryBelgium
CityAntwerp
Period27/08/0731/08/07

Keywords

  • Discriminative noise adaptive training
  • Environment migration

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