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.
Liste complète des métadonnées

https://hal.inria.fr/inria-00528225
Contributeur : Denis Jouvet <>
Soumis le : jeudi 21 octobre 2010 - 11:55:39
Dernière modification le : jeudi 11 janvier 2018 - 06:19:56

Identifiants

  • HAL Id : inria-00528225, version 1

Collections

Citation

Denis Jouvet, Dominique Fohr, Irina Illina. Detailed pronunciation variant modeling for speech transcription. INTERSPEECH, Sep 2010, Makuhari, Japan. 2010, 〈http://www.isca-speech.org/archive/interspeech_2010/i10_2278.html〉. 〈inria-00528225〉

Partager

Métriques

Consultations de la notice

282