Automated Cross-language Intelligibility Analysis of Parkinson’s Disease Patients Using Speech Recognition Technologies

Nina Hosseini-Kivanani, Juan Camilo Vásquez-Correa, Manfred Stede, Elmar Nöth


Abstract
Speech deficits are common symptoms amongParkinson’s Disease (PD) patients. The automatic assessment of speech signals is promising for the evaluation of the neurological state and the speech quality of the patients. Recently, progress has been made in applying machine learning and computational methods to automatically evaluate the speech of PD patients. In the present study, we plan to analyze the speech signals of PD patients and healthy control (HC) subjects in three different languages: German, Spanish, and Czech, with the aim to identify biomarkers to discriminate between PD patients and HC subjects and to evaluate the neurological state of the patients. Therefore, the main contribution of this study is the automatic classification of PD patients and HC subjects in different languages with focusing on phonation, articulation, and prosody. We will focus on an intelligibility analysis based on automatic speech recognition systems trained on these three languages. This is one of the first studies done that considers the evaluation of the speech of PD patients in different languages. The purpose of this research proposal is to build a model that can discriminate PD and HC subjects even when the language used for train and test is different.
Anthology ID:
P19-2010
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Month:
July
Year:
2019
Address:
Florence, Italy
Editors:
Fernando Alva-Manchego, Eunsol Choi, Daniel Khashabi
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
74–80
Language:
URL:
https://aclanthology.org/P19-2010
DOI:
10.18653/v1/P19-2010
Bibkey:
Cite (ACL):
Nina Hosseini-Kivanani, Juan Camilo Vásquez-Correa, Manfred Stede, and Elmar Nöth. 2019. Automated Cross-language Intelligibility Analysis of Parkinson’s Disease Patients Using Speech Recognition Technologies. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 74–80, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Automated Cross-language Intelligibility Analysis of Parkinson’s Disease Patients Using Speech Recognition Technologies (Hosseini-Kivanani et al., ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/P19-2010.pdf