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Communication Dans Un Congrès Année : 1997

Combined models for topic spotting and topic-dependent language modeling

Brigitte Bigi
Marc El-Bèze
  • Fonction : Auteur
Thierry Spriet
  • Fonction : Auteur

Résumé

A new statistical method for Language Modeling and spoken document classification is proposed. It is based on a mixture of topic dependent probabilities. Each topic dependent probability is in turn a mixture of n-gram probabilities and the probability of Kullback-Lieber (KL) distances between keyword unigrams and distribution obtained from the content of a cache memory. Experimental result on topic classification using a corpus of 60 Mword from the French newspaper Le Monde show the excellent performance of the cache memory and its complementary role in providing different statistics for the decision process.
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Dates et versions

hal-01392216 , version 1 (04-11-2016)

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Brigitte Bigi, Renato de Mori, Marc El-Bèze, Thierry Spriet. Combined models for topic spotting and topic-dependent language modeling. IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings, 1997, Santa Barbara, United States. pp.535 - 542, ⟨10.1109/ASRU.1997.659133⟩. ⟨hal-01392216⟩

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