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Conference papers

Support Vector Machines for Keyword Spotting

Yassine Benayed 1 Dominique Fohr 1 Jean-Paul Haton 1 Gérard Chollet 2
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Support Vector Machines is a new and promising technique in statistical learning theory. Recently, this technique produced very interesting results in pattern recognition. In this paper, one of the first application of Support Vector Machines(SVM) technique for the problem of keyword spotting is presented. A two-class SVM approach is first proposed which classifies the correct and the incorrect keywords. The second method uses multi-class SVM, it assigns to each keyword a class label This is a first work proposed to use two-class SVM and multi-class SVin keyword spotting, in order to improve recognition accuracy. The results obtained are very promising.
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Submitted on : Tuesday, September 26, 2006 - 2:52:20 PM
Last modification on : Thursday, January 20, 2022 - 5:26:59 PM


  • HAL Id : inria-00100842, version 1


Yassine Benayed, Dominique Fohr, Jean-Paul Haton, Gérard Chollet. Support Vector Machines for Keyword Spotting. International Workshop speech and computer - SPECOM'2002, Sep 2002, St-Petersburg, Russia, 4 p. ⟨inria-00100842⟩



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