Parameterization of voice onset for automatic assessment of Parkinson’s disease
Arias Vergara T, Schraut T, Orozco-Arroyave JR, Döllinger M (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Original Authors: Tomas Arias-Vergara, Tobias Schraut, Juan R. Orozco-Arroyave, Michael Döllinger
Book Volume: 152
Pages Range: A140-A140
Issue: 4_Supplement
DOI: 10.1121/10.0015820
Abstract
Acoustic analysis of Parkinson’s disease (PD) usually focuses on sustained oscillations of the vocal folds; however, the voice onset (transition from the rest state to a saturation value) is often neglected. In this study, we investigated the parameterization of the voice onset for the objective evaluation of PD. 50 PD patients (25 females) and 50 healthy controls (25 females) performed the sustained phonation of the vowels /ah/, /ih/, and /uh/. Three experts listened to the recordings and assessed the dysarthria level according to a modified version of the Frenchay dysarthria assessment scale (mFDA). We extracted the voice onset automatically, considering the time needed for the amplitude envelope of the acoustic signal to go from 10% up to 90% of the maximum value. Then, we computed filter bank features from the voice onset and pitch, loudness, and perturbation features from the sustained phonation. We performed automatic classification and regression analyses using support vector machines. We obtained a classification accuracy of 89% (AUC: 0.93) when we used feature importance analysis to reduce the feature set. In addition, the regression analysis showed a significant correlation (r: 0.583, p-value < 0.001) between the acoustic features and the mFDA scale. These results show the suitability of the voice onset for objective clinical evaluation of PD.
Authors with CRIS profile
Tomás Arias Vergara
Lehrstuhl für Informatik 5 (Mustererkennung)
Tobias Schraut
Lehrstuhl für Hals-, Nasen- und Ohrenheilkunde
Michael Döllinger
Professur für Computational Medicine (DFG-Forschungsprofessur)
Involved external institutions
Colombia (CO)How to cite
APA:
Arias Vergara, T., Schraut, T., Orozco-Arroyave, J.R., & Döllinger, M. (2022). Parameterization of voice onset for automatic assessment of Parkinson’s disease. Journal of the Acoustical Society of America, 152, A140-A140. https://dx.doi.org/10.1121/10.0015820
MLA:
Arias Vergara, Tomás, et al. "Parameterization of voice onset for automatic assessment of Parkinson’s disease." Journal of the Acoustical Society of America 152 (2022): A140-A140.
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