Keyword Spotting using Support Vector Machines
Identifieur interne : 008611 ( Main/Exploration ); précédent : 008610; suivant : 008612Keyword Spotting using Support Vector Machines
Auteurs : Yassine Benayed ; Dominique Fohr ; Jean-Paul Haton [France] ; Gérard CholletSource :
English descriptors
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.
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Centre national de la recherche scientifique, Institut national de recherche en informatique et en automatique, Laboratoire lorrain de recherche en informatique et ses applications, Université de Lorraine
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