Paper published in a book (Scientific congresses, symposiums and conference proceedings)
EXPLORING THE USE OF PHONOLOGICAL FEATURES FOR PARKINSON’S DISEASE DETECTION
Hosseini Kivanani, Nina; Vásquez-Correa, Juan Camilo; Schommer, Christoph et al.
2023In Hosseini Kivanani, Nina; Vásquez-Correa, Juan Camilo; Schommer, Christoph et al. (Eds.) EXPLORING THE USE OF PHONOLOGICAL FEATURES FOR PARKINSON’S DISEASE DETECTION
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Keywords :
Parkinson’s disease; machine learning models; classification; Phonet; PhonVoc
Abstract :
[en] Parkinson’s disease (PD) is a neurodegenerative disorder that causes motor and non-motor symptoms. Speech impairments are one of the early symptoms of PD, but they are not always fully exploited by clinicians. In this study, the use of phonological features extracted from speech data collected from Spanish-speaking patients was explored to predict PD patients from healthy subjects using phonet, which was trained on Spanish data, and PhonVoc, which was trained on English data. These features were then used to train and test several machine learning models. The XGBoost model achieved the best performance in classifying patients from HCs, with an accuracy of over 0.76. However, the model performed better when using a phonological model trained on Spanish data rather than English data.
Disciplines :
Computer science
Author, co-author :
Hosseini Kivanani, Nina ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Vásquez-Correa, Juan Camilo
Schommer, Christoph  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Nöth, Elmar
External co-authors :
yes
Language :
English
Title :
EXPLORING THE USE OF PHONOLOGICAL FEATURES FOR PARKINSON’S DISEASE DETECTION
Publication date :
August 2023
Event name :
20th International Congress of the Phonetic Sciences (ICPhS 2023)
Event date :
from 07-08-2023 to 11-08-2023
Audience :
International
Main work title :
EXPLORING THE USE OF PHONOLOGICAL FEATURES FOR PARKINSON’S DISEASE DETECTION
Author, co-author :
Hosseini Kivanani, Nina 
Vásquez-Correa, Juan Camilo
Schommer, Christoph  
Nöth, Elmar
Pages :
3897-3901
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 11 September 2023

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