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KOVÁČ, D.
Originální název
Multilingual Analysis of Hypokinetic Dysarthria in Patients with Parkinson's disease
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Acoustic analysis, Parkinson’s disease, hypokinetic dysarthria, classification
Autoři
Vydáno
27. 4. 2021
Místo
BRNO
ISBN
978-80-214-5942-7
Kniha
Proceedings I of the 27st Conference STUDENT EEICT 2021
Strany od
566
Strany do
570
Strany počet
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" }