Deakin University
Browse

File(s) under permanent embargo

Identification of cerebellar dysarthria with SISO characterisation

Version 2 2024-06-02, 13:46
Version 1 2018-05-02, 10:54
conference contribution
posted on 2024-06-02, 13:46 authored by B Kashyap, D Szmulewicz, Pubudu PathiranaPubudu Pathirana, M Horne, L Power
Quantitative identification of dysarthria plays a major role in the classification of its severity. This paper quantitatively analyses several components of cerebellar dysarthria. The methodology described in this study will be extended to other types of dysarthria via systematic analysis. The speech production model is characterized as a second-order single-input and single-output (SISO), linear, time-invariant (LTI) system in our study. A comparative study on the behavior of the damping ratio and resonant frequency for dysarthric and non-dysarthric subjects is presented. The results are further analyzed using the Principal component analysis (PCA) technique to emphasize the variation and uncover strong patterns in the selected features. The effects of some other related factors like decay time and Q-factor are also highlighted.

History

Volume

2018-January

Pagination

479-485

Location

Herndon, Va.

Start date

2017-10-23

End date

2017-10-25

ISSN

2471-7819

eISSN

2471-7819

ISBN-13

978-1-5386-1324-5

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2017, IEEE

Editor/Contributor(s)

O'Conner L

Title of proceedings

BIBE 2017 : Proceedings of the 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering

Event

IEEE Computer Society. Conference (17th : 2017 : Herndon, Va.)

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

Piscataway, N.J.

Series

IEEE Computer Society Conference