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Detailed pronunciation variant modeling for speech transcription

Denis Jouvet 1 Dominique Fohr 1 Irina Illina 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Modeling pronunciation variants is an important topic for automatic speech recognition. This paper investigates the pronunciation modeling at the lexical level, and presents a detailed modeling of the probabilities of the pronunciation variants. The approach is evaluated on the French ESTER2 corpus, and a significant word error rate reduction is achieved through the use of context and speaking rate dependent modeling of these pronunciation probabilities. A rule-based approach makes it possible to derive a priori probabilities for the pronunciation of words that are not present in the training corpus, and a MAP estimation process yields reliable estimates of the pronunciation variant probabilities.
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https://hal.inria.fr/inria-00528225
Contributor : Denis Jouvet <>
Submitted on : Thursday, October 21, 2010 - 11:55:39 AM
Last modification on : Thursday, January 11, 2018 - 6:19:56 AM

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  • HAL Id : inria-00528225, version 1

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Denis Jouvet, Dominique Fohr, Irina Illina. Detailed pronunciation variant modeling for speech transcription. INTERSPEECH, ISCA, Sep 2010, Makuhari, Japan. ⟨inria-00528225⟩

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