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Conference Papers Year : 2002

Keyword Spotting using Support Vector Machines

Dominique Fohr
Gérard Chollet

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. It classifies the correct and the incorrect keywords by using linear and Radial Basis Function kernels. This is a first work proposed to use SVM in keyword spotting, in order to improve recognition and rejection accuracy. The obtained results are very promising.
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Dates and versions

inria-00100835 , version 1 (26-09-2006)

Identifiers

  • HAL Id : inria-00100835 , version 1

Cite

Yassine Benayed, Dominique Fohr, Jean-Paul Haton, Gérard Chollet. Keyword Spotting using Support Vector Machines. Fifth International Conference on Text, Speech and Dialogue - TSD'2002, Sep 2002, Brno, Czech Republic, 8 p. ⟨inria-00100835⟩
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