Multilingual Analysis of Speech and Voice Disorders in Patients with Parkinson's Disease

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU141374" target="_blank" >RIV/00216305:26220/21:PU141374 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/65269705:_____/21:00074860

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9522597" target="_blank" >https://ieeexplore.ieee.org/document/9522597</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TSP52935.2021.9522597" target="_blank" >10.1109/TSP52935.2021.9522597</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multilingual Analysis of Speech and Voice Disorders in Patients with Parkinson's Disease

Popis výsledku v původním jazyce

Parkinson's disease (PD) is associated with several speech/voice disorders collectively referred to as hypokinetic dysarthria (HD). The main goal of this study is to identify acoustic features that support the diagnosis of PD while being independent of the language of a speaker. We recorded seven speech (e.g. monologue) and voice (e.g. sustained phonation) tasks in a cohort of 59 PD patients and 44 age- and gender-matched healthy controls (HC) speaking Czech or US English. A non-parametric test revealed that the best discrimination power has a measure quantifying the number of interword pauses per minute. In a consequent classification analysis, utilising logistic regression, we observed a drop in the classification accuracy from 72-73% to 67%, when moving from single-language modelling to the multilingual one. The results of this study suggest that especially the prosodic (pause-based) features could play a significant role in the automatic language-independent diagnosis of PD.

Název v anglickém jazyce

Multilingual Analysis of Speech and Voice Disorders in Patients with Parkinson's Disease

Popis výsledku anglicky

Parkinson's disease (PD) is associated with several speech/voice disorders collectively referred to as hypokinetic dysarthria (HD). The main goal of this study is to identify acoustic features that support the diagnosis of PD while being independent of the language of a speaker. We recorded seven speech (e.g. monologue) and voice (e.g. sustained phonation) tasks in a cohort of 59 PD patients and 44 age- and gender-matched healthy controls (HC) speaking Czech or US English. A non-parametric test revealed that the best discrimination power has a measure quantifying the number of interword pauses per minute. In a consequent classification analysis, utilising logistic regression, we observed a drop in the classification accuracy from 72-73% to 67%, when moving from single-language modelling to the multilingual one. The results of this study suggest that especially the prosodic (pause-based) features could play a significant role in the automatic language-independent diagnosis of PD.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/NU20-04-00294" target="_blank" >NU20-04-00294: Diagnostika onemocnění s Lewyho tělísky v prodromálním stadiu založená na analýze multimodálních dat</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2021 44th International Conference on Telecommunications and Signal Processing

ISBN

978-1-6654-2933-7

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

273-277

Název nakladatele

IEEE

Místo vydání

NEW YORK

Místo konání akce

Brno

Datum konání akce

26. 7. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000701604600059