Influence of delay time on regularity estimation for voice pathology detection

Godino Llorente, Juan Ignacio; Gómez García, J.A. y Castellanos Dominguez, G. (2012). Influence of delay time on regularity estimation for voice pathology detection. En: "34th Annual International Conference of the IEEE EMBS San Diego, California USA, 28 August - 1 September, 2012", 28/08/2012 al 1/09/2012, San Diego (California). ISBN 978-1-4577-1787-1.

Descripción

Título: Influence of delay time on regularity estimation for voice pathology detection
Autor/es:
  • Godino Llorente, Juan Ignacio
  • Gómez García, J.A.
  • Castellanos Dominguez, G.
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 34th Annual International Conference of the IEEE EMBS San Diego, California USA, 28 August - 1 September, 2012
Fechas del Evento: 28/08/2012 al 1/09/2012
Lugar del Evento: San Diego (California)
Título del Libro: 34th Annual International Conference of the IEEE EMBS San Diego, California USA, 28 August - 1 September, 2012
Fecha: 2012
ISBN: 978-1-4577-1787-1
Materias:
Escuela: E.U.I.T. Telecomunicación (UPM) [antigua denominación]
Departamento: Ingeniería de Circuitos y Sistemas [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The employment of nonlinear analysis techniques for automatic voice pathology detection systems has gained popularity due to the ability of such techniques for dealing with the underlying nonlinear phenomena. On this respect, characterization using nonlinear analysis typically employs the classical Correlation Dimension and the largest Lyapunov Exponent, as well as some regularity quantifiers computing the system predictability. Mostly, regularity features highly depend on a correct choosing of some parameters. One of those, the delay time �, is usually fixed to be 1. Nonetheless, it has been stated that a unity � can not avoid linear correlation of the time series and hence, may not correctly capture system nonlinearities. Therefore, present work studies the influence of the � parameter on the estimation of regularity features. Three � estimations are considered: the baseline value 1; a � based on the Average Automutual Information criterion; and � chosen from the embedding window. Testing results obtained for pathological voice suggest that an improved accuracy might be obtained by using a � value different from 1, as it accounts for the underlying nonlinearities of the voice signal.

Más información

ID de Registro: 20301
Identificador DC: http://oa.upm.es/20301/
Identificador OAI: oai:oa.upm.es:20301
Depositado por: Memoria Investigacion
Depositado el: 14 Mar 2014 07:41
Ultima Modificación: 21 Abr 2016 23:03
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