Unobtrusive Monitoring of Speech Impairments of Parkinson'S Disease Patients Through Mobile Devices
Tomás Arias-Vergara, Juan Camilo Vásquez-Correa, Juan Rafael Orozco-Arroyave, Philipp Klumpp, Elmar Nöth
Abstract
Parkinson's disease (PD) produces several speech impairments in the patients. Automatic classification of PD patients is performed considering speech recordings collected in noncontrolled acoustic conditions during normal phone calls in a unobtrusive way. A speech enhancement algorithm is applied to improve the quality of the signals. Two different classification approaches are considered: the classification of PD patients and healthy speakers and a multi-class experiment to classify patients in several stages of the disease. According to the results it is possible to classify PD patients and healthy controls with a AUe of up to 0.87. This work is a step forward to the development of telemonitoring systems to assess the speech of the patients.
BibTeX
@inproceedings{icassp2018_unobtrusivemonit,
title = {Unobtrusive Monitoring of Speech Impairments of Parkinson'S Disease Patients Through Mobile Devices},
author = {Tomás Arias-Vergara and Juan Camilo Vásquez-Correa and Juan Rafael Orozco-Arroyave and Philipp Klumpp and Elmar Nöth},
booktitle = {ICASSP 2018},
year = {2018}
}