Descripción
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This paper presents the application of a feature selection technique such as LDA to a language identification (LID) system. The baseline system consists of a PPRLM module followed by a multiple-Gaussian classifier. This classifier makes use of acoustic scores and duration features of each input utterance. We applied a dimension reduction of the feature space in order to achieve a faster and easier-trainable system. We imputed missing values of our vectors before projecting them on the new space. Our experiments show a very low performance reduction due to the dimension reduction approach. Using a single dimension projection the error rates we have obtained are about 8.73% taking into account the 22 most significant features. | |
Internacional
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No |
Nombre congreso
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V Jornadas de Tecnología del Habla |
Tipo de participación
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960 |
Lugar del congreso
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Bilbao |
Revisores
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Si |
ISBN o ISSN
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978-84-9860-169-5 |
DOI
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Fecha inicio congreso
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12/11/2008 |
Fecha fin congreso
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14/11/2008 |
Desde la página
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29 |
Hasta la página
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32 |
Título de las actas
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Actas de V Jornadas de Tecnología del Habla |