Are speech attractor models useful in diagnosing vocal fold pathologies?

Abstract

The speech is an easily accessible signal which clearly represents the characteristics of larynx and vocal folds. Therefore, application of some proper machine learning algorithms on a small part of a recorded speech signal may help in non-invasive diagnosing of vocal fold diseases. Since there are some experimental evidences that suggest the existence of chaotic behavior in speech production system, in this paper a new method is proposed to predict vocal fold pathologies using its chaotic characteristics. The proposed method is based on modeling of pathological voice as a speech trajectory in the reconstructed phase space.