Presentation | 1994/1/21 On-line Speaker Adaptation using Maximum a posteriori Estimation Tatsuo Matsuoka, Chin-Hui Lee, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper,we study issues related to the use of on-line incremental adaptation for speech recognition.We apply the MAP estimation that uses conjugate prior as prior distribution.That conjugate prior is known as sufficient statistics for exponential family.We use the segmental MAP algorithm to perform HMM adaptation.Two modes of incremental adaptation,namely supervised and unsupervised adaptation,are tested.In the supervised mode,the correct word transcription is used for MAP adaptation,while in the unsupervised mode,the word transcription is provided by the recognizer.We report on the results obtained for the ARPA Air Travel Information stem(ATIS)task.Compared with the speaker independent recognition results,the supervised and unsupervised incremental adaptation algorithms reduce the word error rate by 25% and 5.6% respectively. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | speaker adaptation / hidden Markov model(HMM) / maximum aposteriori estimation(MAP) |
Paper # | SP93-133 |
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Committee | SP |
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Conference Date | 1994/1/21(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Speech (SP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | On-line Speaker Adaptation using Maximum a posteriori Estimation |
Sub Title (in English) | |
Keyword(1) | speaker adaptation |
Keyword(2) | hidden Markov model(HMM) |
Keyword(3) | maximum aposteriori estimation(MAP) |
1st Author's Name | Tatsuo Matsuoka |
1st Author's Affiliation | NTT Laboratories() |
2nd Author's Name | Chin-Hui Lee |
2nd Author's Affiliation | AT&T Bell Laboratories |
Date | 1994/1/21 |
Paper # | SP93-133 |
Volume (vol) | vol.93 |
Number (no) | 427 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |