InforLorV4, Hal, Corpus, bibRecord, 000609

A complete understanding speech system based on semantic concepts

Identifieur interne : 000609 ( Hal/Corpus ); précédent : 000608; suivant : 000610

A complete understanding speech system based on semantic concepts

Auteurs : Salma Jamoussi ; Kamel Smaïli ; Dominique Fohr ; Jean-Paul Haton

Source :

RBID : Hal:inria-00100086

Descripteurs français

mix :
- autoclass.

English descriptors

mix :
- automatic extraction of concepts, bayesian networks, classification non supervisée, clustering methods, compréhension de la parole, extraction automatique des concepts, mesures sémantiques, représentation vectorielle des mots, réseaux bayésiens, semantic measures, speech understanding, word vector representation.

Abstract

In this work, we present a complete speech understanding system based on our speech recognizer: ESPERE. The input signal is processed and the best sentence is then proposed to the understanding module. In our case, the understanding problem is considered as a matching process between two different languages. At the entry, the request expressed in natural language and at the output the corresponding SQL form. The SQL request is obtained after an intermediate step in which the entry is expressed in terms of concepts. A concept represents a given meaning, it is defined by a set of words sharing the same semantic properties. In this paper, we propose a new Bayesian classifier to automatically extract the underlined concepts. We also propose a new approach for vector representation of words. Then, we describe the postprocessing step during which, we label our sentences and we generate the corresponding SQL queries. We conclude our paper by describing the integration step of our understanding module in a complete platform of human-machine oral intercation.

Url:

https://hal.inria.fr/inria-00100086

Links to Exploration step

Hal:inria-00100086

Le document en format XML

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   |texte=   A complete understanding speech system based on semantic concepts
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A complete understanding speech system based on semantic concepts

A complete understanding speech system based on semantic concepts

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