Publication detail

Multilingual Analysis of Hypokinetic Dysarthria in Patients with Parkinson's disease

KOVÁČ, D.

Original Title

Multilingual Analysis of Hypokinetic Dysarthria in Patients with Parkinson's disease

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This article deals with the multilingual analysis of hypokinetic dysarthria (HD) in patients with Parkinson’s disease (PD). The goal is to identify acoustic features that have high discrimination power and that are independent of the language of a speaker. The speech corpus contains 59 PD patients and 44 healthy controls (HC) speaking in Czech (cs) and American English (en-US). Based on non-parametric statistical tests and logistic regression, we observed the best discrimination power has the speech index of rhythmicity (extracted from a reading text) and harmonic-to-noise ratio (extracted from a sustained vowel). We were able to identify PD with 67% sensitivity and 79% specificity in the Czech corpus and with 78% sensitivity and 67% specificity in the English one. The performance of the model was significantly lower when combining both datasets, thus suggesting language plays a significant role during the automatic assessment of HD.

Keywords

Acoustic analysis, Parkinson’s disease, hypokinetic dysarthria, classification

Authors

KOVÁČ, D.

Released

27. 4. 2021

Location

BRNO

ISBN

978-80-214-5942-7

Book

Proceedings I of the 27st Conference STUDENT EEICT 2021

Pages from

566

Pages to

570

Pages count

5

URL

https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_1.pdf

BibTex

@inproceedings{BUT172145,
  author="Daniel {Kováč}",
  title="Multilingual Analysis of Hypokinetic Dysarthria in Patients with Parkinson's disease",
  booktitle="Proceedings I of the 27st Conference STUDENT EEICT 2021",
  year="2021",
  pages="566--570",
  address="BRNO",
  isbn="978-80-214-5942-7",
  url="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_1.pdf"
}