ISCA Archive NOLISP 2005
ISCA Archive NOLISP 2005

Using nonlinear features for voice disorder detection

Jesús B. Alonso, Fernando Díaz-de-María, Carlos M. Travieso, Miguel Angel Ferrer

In this paper we propose the use of nonlinear speech features to improve the voice quality measurement. We have tested a couple of features from the Dynamical System Theory, namely: the Correlation Dimension and the largest Lyapunov Exponent. In particular, we have studied the optimal size of time window for this type of analysis in the field of the characterization of the voice quality. Two systems of automatic detection of laryngeal pathologies, one of them including these features, have been implemented with the purpose of validating the usefulness of the suggested nonlinear features. We obtain slight improvements with respect to a classical system.