Original title:
Multilingual Analysis Of Hypokinetic Dysarthria In Patients With Parkinson’s Disease
Authors:
Kováč, Daniel Document type: Papers
Language:
eng Publisher:
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií Abstract:
This article deals with the multilingual analysis of hypokinetic dysarthria (HD) in patientswith Parkinson’s disease (PD). The goal is to identify acoustic features that have high discriminationpower and that are independent of the language of a speaker. The speech corpus contains 59 PD patientsand 44 healthy controls (HC) speaking in Czech (cs) and American English (en-US). Based onnon-parametric statistical tests and logistic regression, we observed the best discrimination power hasthe speech index of rhythmicity (extracted from a reading text) and harmonic-to-noise ratio (extractedfrom a sustained vowel). We were able to identify PD with 67% sensitivity and 79% specificity inthe Czech corpus and with 78% sensitivity and 67% specificity in the English one. The performanceof the model was significantly lower when combining both datasets, thus suggesting language playsa significant role during the automatic assessment of HD.
Keywords:
Acoustic analysis; classification; hypokinetic dysarthria; Parkinson’s disease Host item entry: Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers, ISBN 978-80-214-5942-7
Institution: Brno University of Technology
(web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library. Original record: http://hdl.handle.net/11012/200696