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Original title:
Assessing Movement of Articulatory Organs in Patients with Parkinson’s Disease
Authors: Novotný, K. ; Mekyska, J.
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: Hypokinetic dysarthria is a motor speech disorder often present during Parkinson’s disease. It affects the speech system, including articulatory abilities. There are several speech parameters describing this domain, so it is suggested to deal with their mutual comparison. This work aims to design and describe an algorithm for calculating the parameters of articulation, adapted for the Czech language, and then compare their discriminative power. The acoustic analysis of speech included in it is done via the Praat program and basic machine learning algorithms such as Expectation-Maximization, K-means and linear regression are used for the subsequent data processing. The Mann-Whitney U test, descriptive statistics and Random Forest machine learning model using cross-validation and balanced accuracy is used for evaluation. The results are scripts for automatic assessment of vowel space area, for calculating articulation parameters and for their evaluation. The outputs of the analysis of speech recording database prove that differences in articulation can indeed be observed between normal and dysarthric speech. Based on the mutual comparison of results, it is therefore proposed in the work which parameters are being appropriate for further dealing with this issue.
Keywords: acoustic analysis; articulation; formant frequencies; Hypokinetic dysarthria; machine learning; speech parametrization; speech signal processing
Host item entry: Proceedings I of the 28st Conference STUDENT EEICT 2022: General papers, ISBN 978-80-214-6029-4
Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/209337
Permalink: http://www.nusl.cz/ntk/nusl-524764
The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers
Authors: Novotný, K. ; Mekyska, J.
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: Hypokinetic dysarthria is a motor speech disorder often present during Parkinson’s disease. It affects the speech system, including articulatory abilities. There are several speech parameters describing this domain, so it is suggested to deal with their mutual comparison. This work aims to design and describe an algorithm for calculating the parameters of articulation, adapted for the Czech language, and then compare their discriminative power. The acoustic analysis of speech included in it is done via the Praat program and basic machine learning algorithms such as Expectation-Maximization, K-means and linear regression are used for the subsequent data processing. The Mann-Whitney U test, descriptive statistics and Random Forest machine learning model using cross-validation and balanced accuracy is used for evaluation. The results are scripts for automatic assessment of vowel space area, for calculating articulation parameters and for their evaluation. The outputs of the analysis of speech recording database prove that differences in articulation can indeed be observed between normal and dysarthric speech. Based on the mutual comparison of results, it is therefore proposed in the work which parameters are being appropriate for further dealing with this issue.
Keywords: acoustic analysis; articulation; formant frequencies; Hypokinetic dysarthria; machine learning; speech parametrization; speech signal processing
Host item entry: Proceedings I of the 28st Conference STUDENT EEICT 2022: General papers, ISBN 978-80-214-6029-4
Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/209337
Permalink: http://www.nusl.cz/ntk/nusl-524764
The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers
Record created 2023-05-07, last modified 2023-05-07