Vers une modélisation statistique multi-niveau du langage, application aux langues peu dotées. (Toward a multi-level statistical language modeling for under-resourced language)

Ce travail de these porte sur la reconnaissance automatique de la parole des langues peu dotees et ayant un systeme d'ecriture sans separation explicite entre les mots. La specificite des langues traitees dans notre contexte d'etude necessite la segmentation automatique en mots pour rendre la modelisation du langage n-gramme applicable. Alors que le manque de donnees textuelles a un impact sur la performance des modeles de langage, les erreurs introduites par la segmentation automatique peuvent rendre ces donnees encore moins exploitables. Pour tenter de pallier les problemes, nos recherches sont axees principalement sur la modelisation du langage, et en particulier sur le choix des unites lexicales et sous-lexicales, utilisees par les systemes de reconnaissance. Nous experimentons l'utilisation des multiples unites au niveau des modeles du langage et au niveau des sorties de systemes de reconnaissance. Nous validons ces approches de modelisation a base des multiples unites sur les systemes de reconnaissance pour un groupe de langues peu dotees : le khmer, le vietnamien, le thai et le laotien.

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