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.
Document type :
Conference papers
Complete list of metadatas

Cited literature [10 references]  Display  Hide  Download

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
Long-term archiving on: Friday, November 25, 2016 - 1:04:41 PM

Licence


Public Domain

Identifiers

  • HAL Id : inria-00107536, version 1

Collections

Citation

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. ⟨inria-00107536⟩

Share

Metrics

Record views

366

Files downloads

118