A Hierarchical Approach for Topic Identification

Brigitte Bigi 1 Armelle Brun 1 Kamel Smaïli 1 Jean-Paul Haton 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper focuses on language model adaptation, and more especially on topic identification (TID) for Automatic Speech Recognition (ASR). The structure of a set of topics is redefined by the introduction of a hierarchy. TID models may then make use of the semantic relationships between parent and son nodes of the topic-tree. The originality of the approach presented in this article lies in the allocation of a unique vocabulary to brother nodes, which rests on the use of two backing-off levels. In comparison with TID performance when using a non-hierarchical approach, results encourage us to carry on in this way.
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Communication dans un congrès
Proceedings of the international workshop Speech and Computer - SPECOM'01, Nov 2001, Moscow, Russia, France. 4 p, 2001
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Dernière modification le : jeudi 11 janvier 2018 - 06:19:55
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Brigitte Bigi, Armelle Brun, Kamel Smaïli, Jean-Paul Haton. A Hierarchical Approach for Topic Identification. Proceedings of the international workshop Speech and Computer - SPECOM'01, Nov 2001, Moscow, Russia, France. 4 p, 2001. 〈inria-00107536〉

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