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A Hierarchical Approach for Topic Identification
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.
Cited literature [10 references]
https://hal.inria.fr/inria-00107536
Contributor : Publications Loria <>
Submitted on : Thursday, October 19, 2006 - 9:00:24 AM
Last modification on : Thursday, January 11, 2018 - 6:19:55 AM
Document(s) archivé(s) le : Friday, November 25, 2016 - 1:04:41 PM
Contributor : Publications Loria <>
Submitted on : Thursday, October 19, 2006 - 9:00:24 AM
Last modification on : Thursday, January 11, 2018 - 6:19:55 AM
Document(s) archivé(s) le : Friday, November 25, 2016 - 1:04:41 PM