Exploiting nonlinearity of the speech production system for voice disorder assessment by recurrence quantification analysis
Vinícius Jefferson Dias Vieira, Silvana Luciene Do Nascimento Cunha Costa, Suzete Correia, Leonardo Wanderley Lopes, Washington C. de A. Costa, Francisco de Assis · Chaos An Interdisciplinary Journal of Nonlinear Science · 2018
This work summarizes the research related to digital speech signal processing with recurrence quantification analysis (RQA) applied to voice disorder assessment. The main motivation for these studies is the fact that RQA is able to exploit the nonlinear dynamical nature of the speech production system. Due to the use of recurrence quantification measures to represent the behavior of speech signals, promising results were obtained in the characterization and classification of laryngeal pathologies and voice disorders. These contributions may help one to evaluate the usability and efficiency of RQA in vocal disorder assessment.