Selección de características usando hmm para la identificación de patologías de voz


Authors

  • Mauricio Álvarez
  • Germán Castellanos

Abstract

Aunque se conocen diversos métodos de selección de características, orientados al mejor rendimiento de clasificación, en el caso de los procesos aleatorios markovianos, la reducción en la dimensionalidad del hiperespacio inicial de entrenamiento es compleja, por cuanto cada característica corresponde a un vector con dinámica de cambio propia. En el presente trabajo se analizan dos alternativas para selección de las características: Análisis de Componentes Principales y Análisis Discriminante Lineal. Los resultados obtenidos muestran un rendimiento de clasificación entre 76.25% y 91.45%.

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Published

2005-01-10

How to Cite

Álvarez, M., & Castellanos, G. (2005). Selección de características usando hmm para la identificación de patologías de voz. Scientia Et Technica, 2(28). Retrieved from https://revistas.utp.edu.co/index.php/revistaciencia/article/view/6815

Issue

Vol. 2 No. 28 (2005)

Section

Eléctrica

License

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