Automatic detection of pathologies in the voice by HOS based parameters
EURASIP Journal on Applied Signal Processing - Nonlinear signal and image processing - part I
Evaluation of Neural Classifiers using Statistic Methods for Identification of Laryngeal Pathologies
SBRN '98 Proceedings of the Vth Brazilian Symposium on Neural Networks
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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.