Modeling fundamental frequency dynamics in hypokinetic dysarthria

Mahsa Sadat Elyasi Langarani; Jan Van Santen

doi:10.1109/SLT.2014.7078586

Modeling fundamental frequency dynamics in hypokinetic dysarthria

Mahsa Sadat Elyasi Langarani, Jan Van Santen

Institute on Development and Disability

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

Hypokinetic dysarthria (Hd), which often accompanies Parkinson's Disease (PD), is characterized by hypernasality and by compromised phonation, prosody, and articulation. This paper proposes automated methods for detection of Hd. Whereas most such studies focus on measures of phonation, this paper focuses on prosody, specifically on fundamental frequency (F0) dynamics. Prosody in Hd is clinically described as involving monopitch, which has been confirmed in numerous studies reporting reduced within-utterance pitch variability. We show that a new measure of F0 dynamics, based on a superpositional pitch model that decomposes the F0 contour into a declining phrase curve and (generally, single-peaked) accent curves, performs more accurate Hd vs. Control classification than simpler versions of the model or than conventional variability statistics.

Original language	English (US)
Title of host publication	2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	272-276
Number of pages	5
ISBN (Electronic)	9781479971299
DOIs	https://doi.org/10.1109/SLT.2014.7078586
State	Published - Apr 1 2014
Event	2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - South Lake Tahoe, United States Duration: Dec 7 2014 → Dec 10 2014

Publication series

Name	2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings

Other

Other	2014 IEEE Workshop on Spoken Language Technology, SLT 2014
Country/Territory	United States
City	South Lake Tahoe
Period	12/7/14 → 12/10/14

Keywords

Hypokinetic dysarthria
Parkinson's Disease
Pitch decomposition

ASJC Scopus subject areas

Computer Science Applications
Human-Computer Interaction
Computer Vision and Pattern Recognition
Artificial Intelligence
Language and Linguistics

Access to Document

10.1109/SLT.2014.7078586

Cite this

Langarani, M. S. E., & Van Santen, J. (2014). Modeling fundamental frequency dynamics in hypokinetic dysarthria. In 2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings (pp. 272-276). Article 7078586 (2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SLT.2014.7078586

Modeling fundamental frequency dynamics in hypokinetic dysarthria. / Langarani, Mahsa Sadat Elyasi; Van Santen, Jan.
2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 272-276 7078586 (2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Langarani, MSE & Van Santen, J 2014, Modeling fundamental frequency dynamics in hypokinetic dysarthria. in 2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings., 7078586, 2014 IEEE Workshop on Spoken Language Technology, SLT 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 272-276, 2014 IEEE Workshop on Spoken Language Technology, SLT 2014, South Lake Tahoe, United States, 12/7/14. https://doi.org/10.1109/SLT.2014.7078586

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AB - Hypokinetic dysarthria (Hd), which often accompanies Parkinson's Disease (PD), is characterized by hypernasality and by compromised phonation, prosody, and articulation. This paper proposes automated methods for detection of Hd. Whereas most such studies focus on measures of phonation, this paper focuses on prosody, specifically on fundamental frequency (F0) dynamics. Prosody in Hd is clinically described as involving monopitch, which has been confirmed in numerous studies reporting reduced within-utterance pitch variability. We show that a new measure of F0 dynamics, based on a superpositional pitch model that decomposes the F0 contour into a declining phrase curve and (generally, single-peaked) accent curves, performs more accurate Hd vs. Control classification than simpler versions of the model or than conventional variability statistics.

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Modeling fundamental frequency dynamics in hypokinetic dysarthria

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Keywords

ASJC Scopus subject areas

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