Artículo
Genetic wavelet packets for speech recognition
Fecha de publicación:
05/2013
Editorial:
Elsevier
Revista:
Expert Systems With Applications
ISSN:
0957-4174
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The most widely used speech representation is based on the mel-frequency cepstral coefficients, which incorporates biologically inspired characteristics into artificial recognizers. However, the recognition performance with these features can still be enhanced, specially in adverse conditions. Recent advances have been made with the introduction of wavelet based representations for different kinds of signals, which have shown to improve the classification performance. However, the problem of finding an adequate wavelet based representation for a particular problem is still an important challenge. In this work we propose a genetic algorithm to evolve a speech representation, based on a non-orthogonal wavelet decomposition, for phoneme classification. The results, obtained for a set of spanish phonemes, show that the proposed genetic algorithm is able to find a representation that improves speech recognition results. Moreover, the optimized representation was evaluated in noise conditions.
Palabras clave:
Phoneme Classification
,
Genetic Algorithms
,
Wrappers
,
Wavelet Packets
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos(CCT - SANTA FE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Citación
Vignolo, Leandro Daniel; Milone, Diego Humberto; Rufiner, Hugo Leonardo; Genetic wavelet packets for speech recognition; Elsevier; Expert Systems With Applications; 40; 6; 5-2013; 2350-2359
Compartir
Altmétricas