The Impact of Lexical and Articulatory Factors in the Automatic Selection of Test Materials for a Web-Based Assessment of Intelligibility in Dysarthria
Publication: Journal of Speech, Language, and Hearing Research
Volume 64, Number 6S
Pages 2196-2212
Abstract
Purpose
The clinical assessment of intelligibility must be based on a large repository and extensive variation of test materials, to render test stimuli unpredictable and thereby avoid expectancies and familiarity effects in the listeners. At the same time, it is essential that test materials are systematically controlled for factors influencing intelligibility. This study investigated the impact of lexical and articulatory characteristics of quasirandomly selected target words on intelligibility in a large sample of dysarthric speakers under clinical examination conditions.
Method
Using the clinical assessment tool KommPaS, a total of 2,700 sentence-embedded target words, quasirandomly drawn from a large corpus, were spoken by a group of 100 dysarthric patients and later transcribed by listeners recruited via online crowdsourcing. Transcription accuracy was analyzed for influences of lexical frequency, phonological neighborhood structure, articulatory complexity, lexical familiarity, word class, stimulus length, and embedding position. Classification and regression analyses were performed using random forests and generalized linear mixed models.
Results
Across all degrees of severity, target words with higher frequency, fewer and less frequent phonological neighbors, higher articulatory complexity, and higher lexical familiarity received significantly higher intelligibility scores. In addition, target words were more challenging sentence-initially than in medial or final position. Stimulus length had mixed effects; word length and word class had no effect.
Conclusions
In a large-scale clinical examination of intelligibility in speakers with dysarthria, several well-established influences of lexical and articulatory parameters could be replicated, and the roles of new factors were discussed. This study provides clues about how experimental rigor can be combined with clinical requirements in the diagnostics of communication impairment in patients with dysarthria.
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Information & Authors
Information
Published In
Journal of Speech, Language, and Hearing Research
Volume 64 • Number 6S • June 2021
Pages: 2196-2212
PubMed: 33647214
Copyright
Copyright © 2021 American Speech-Language-Hearing Association.
History
- Received: May 18, 2020
- Revised: Jul 6, 2020
- Accepted: Aug 13, 2020
- Published online: Mar 1, 2021
- Published in issue: Jun 18, 2021
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- Afnan Al-Ali, Somaya Al-Maadeed, Moutaz Saleh, Rani Chinnappa Naidu, Zachariah C. Alex, Prakash Ramachandran, Rajeev Khoodeeram, Rajesh Kumar M, The Detection of Dysarthria Severity Levels Using AI Models: A Review, IEEE Access, 10.1109/ACCESS.2024.3382574, 12, (48223-48238), (2024).
- Vera Wolfrum, Katharina Lehner, Stefan Heim, Wolfram Ziegler, Clinical Assessment of Communication-Related Speech Parameters in Dysarthria: The Impact of Perceptual Adaptation, Journal of Speech, Language, and Hearing Research, 10.1044/2023_JSLHR-23-00105, 66, 8, (2622-2642), (2023).
- Kaila L. Stipancic, Gregory Wilding, Kris Tjaden, Lexical Characteristics of the Speech Intelligibility Test: Effects on Transcription Intelligibility for Speakers With Multiple Sclerosis and Parkinson's Disease, Journal of Speech, Language, and Hearing Research, 10.1044/2023_JSLHR-22-00279, 66, 8S, (3115-3131), (2023).
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