Abstract
This paper presents preliminary results of individual speaker models for monitoring Parkinson’s disease from speech using a smart-phone. The aim of this study is to evaluate the suitability of mobile devices to perform robust speech analysis. Speech recordings from 68 PD patients were captured from 2012 to 2016 in four recording sessions. The performance of the speaker models is evaluated according to two clinical rating scales: the Unified Parkinson’s Diseae Rating Scale (UPDRS) and a modified version of the Frenchay Dysarthria Assessment (m-FDA) scale. According to the results, it is possible to assess the disease progression from speech with Pearson’s correlations of up to \(r=0.51\). This study suggests that it is worth to continue working on the development of mobile-based tools for the continuous and unobtrusive monitoring of Parkinson’s patients.
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Acknowledgments
This work was financed by COLCIENCIAS through the project No 111556933858. The work reported here was started at JSALT 2016, and was supported by JHU via grants from DARPA (LORELEI), Microsoft, Amazon, Google and Facebook. Thanks also to CODI from University of Antioquia by the grant Numbers 2015–7683 and PRV16-2-01.
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Arias-Vergara, T., Klumpp, P., Vásquez-Correa, J.C., Orozco-Arroyave, J.R., Nöth, E. (2017). Parkinson’s Disease Progression Assessment from Speech Using a Mobile Device-Based Application. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_42
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DOI: https://doi.org/10.1007/978-3-319-64206-2_42
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