Presentation 2005/12/15
Utterance-based Selective Training for Task-Dependent Acoustic Modeling
Tobias CINCAREK, Tomoki TODA, Hiroshi SARUWATARI, Kiyohiro SHIKANO,
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Abstract(in English) Large amounts of speech data are necessary to construct high performance acoustic models. Since speech recognition performance is task-dependent and the effort and costs for speech data collection and transcription are very high, it is infeasable to prepare enough data for every new application which makes use of speech recognition technology. In this paper an algorithm for utterance-based selective training is proposed, which enables the automatic and cost-effective construction of task-dependent acoustic models. Training utterances are selected from existing speech data resources so that the likelihood of an independent development data set is maximized. Fast calculation of the likelihood is possible with sufficient statistics. The algorithm is evaluated for constructing an infant-dependent model with speech from elementary school children and an elderly-dependent model with adult speech data. Selective training is already effective with only ten development utterances. Furthermore, a higher word accuracy than with the standard adaptation methods MAP and MLLR was achieved.
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Keyword(in English) Acoustic Modeling / Task-Dependency / Cost Reduction / Selective Training / Sufficient Statistics
Paper # NLC2005-102,SP2005-135
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Committee NLC
Conference Date 2005/12/15(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Utterance-based Selective Training for Task-Dependent Acoustic Modeling
Sub Title (in English)
Keyword(1) Acoustic Modeling
Keyword(2) Task-Dependency
Keyword(3) Cost Reduction
Keyword(4) Selective Training
Keyword(5) Sufficient Statistics
1st Author's Name Tobias CINCAREK
1st Author's Affiliation Nara Institute of Science and Technology()
2nd Author's Name Tomoki TODA
2nd Author's Affiliation Nara Institute of Science and Technology
3rd Author's Name Hiroshi SARUWATARI
3rd Author's Affiliation Nara Institute of Science and Technology
4th Author's Name Kiyohiro SHIKANO
4th Author's Affiliation Nara Institute of Science and Technology
Date 2005/12/15
Paper # NLC2005-102,SP2005-135
Volume (vol) vol.105
Number (no) 494
Page pp.pp.-
#Pages 6
Date of Issue