LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

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Title MHATLex: Lexical Resources for Modelling the French Pronunciation

Authors Perennou Guy (Institut de Recherche en Informatique, Universite Paul Sabatier, 118,route de Narbonne, 31062 Toulouse Cedex France, perennou@irit.fr)
De Calmes Martine (Institut de Recherche en Informatique, Universite Paul Sabatier, 118,route de Narbonne, 31062 Toulouse Cedex France, decalmes@irit.fr)

Keywords ASR, Lexical Resources, Pronunciation Model

Session Session SP1 - Phonetic Issues and Speech Synthesis

Abstract The aim of this paper is to introduce the lexical resources and environment, called MHATLex, and intended for speech and text processing. A particular attention is paid to a pronunciation modelling which can be used in automatic speech processing as well as in phonological/phonetic description of languages. In our paper we will introduce a pronunciation model, the MHAT model (Markovian Harmonic Adaptation and Transduction), which copes with free and context-dependent variants. At the same time, we will present the MHATLex resources. They include 500,000 inflected forms and tools allowing the generation of various lexicons through phonological tables. Finally, some illustrations of the use of MHATLex in ASR will be shown.

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Title	MHATLex: Lexical Resources for Modelling the French Pronunciation
Authors	Perennou Guy (Institut de Recherche en Informatique, Universite Paul Sabatier, 118,route de Narbonne, 31062 Toulouse Cedex France, perennou@irit.fr) De Calmes Martine (Institut de Recherche en Informatique, Universite Paul Sabatier, 118,route de Narbonne, 31062 Toulouse Cedex France, decalmes@irit.fr)
Keywords	ASR, Lexical Resources, Pronunciation Model
Session	Session SP1 - Phonetic Issues and Speech Synthesis
Abstract	The aim of this paper is to introduce the lexical resources and environment, called MHATLex, and intended for speech and text processing. A particular attention is paid to a pronunciation modelling which can be used in automatic speech processing as well as in phonological/phonetic description of languages. In our paper we will introduce a pronunciation model, the MHAT model (Markovian Harmonic Adaptation and Transduction), which copes with free and context-dependent variants. At the same time, we will present the MHATLex resources. They include 500,000 inflected forms and tools allowing the generation of various lexicons through phonological tables. Finally, some illustrations of the use of MHATLex in ASR will be shown.