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Speaker adaptation for hybrid MMI/connectionist speech-recognition systems

  • University of Duisburg-Essen

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

6 Scopus citations

Abstract

We present a new adaptation technique for our hybrid large vocabulary continuous speech recognition system. In most adaptation approaches the HMM parameters are reestimated. In our approach, however, we train a speaker independent continuous speech recognizer, then we keep the HMM parameters fixed and we train a second network, which transforms the features of the adaptation data to fit the HMM parameters. Thus, less parameters have to be estimated, and therefore this approach performs well even for a small number of adaptation data. With this approach we achieve relative improvements in recognition rates on the Wall Street Journal (WSJ) task of 16.5%.

Original languageEnglish
Title of host publicationProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages465-468
Number of pages4
ISBN (Print)0780344286, 9780780344280
DOIs
StatePublished - 1998
Externally publishedYes
Event1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 - Seattle, WA, United States
Duration: 12 May 199815 May 1998

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume1
ISSN (Print)1520-6149

Conference

Conference1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
Country/TerritoryUnited States
CitySeattle, WA
Period12/05/9815/05/98

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