Illner, Vojtech; Tykalova, Tereza; Skrabal, Dominik; Klempir, Jiri; Rusz, Jan (2023). Automated Vowel Articulation Analysis in Connected Speech Among Progressive Neurological Diseases, Dysarthria Types, and Dysarthria Severities. Journal of speech, language, and hearing research : JSLHR, 66(8), pp. 2600-2621. American Speech-Language-Hearing Association 10.1044/2023_JSLHR-22-00526
Full text not available from this repository.PURPOSE
Although articulatory impairment represents distinct speech characteristics in most neurological diseases affecting movement, methods allowing automated assessments of articulation deficits from the connected speech are scarce. This study aimed to design a fully automated method for analyzing dysarthria-related vowel articulation impairment and estimate its sensitivity in a broad range of neurological diseases and various types and severities of dysarthria.
METHOD
Unconstrained monologue and reading passages were acquired from 459 speakers, including 306 healthy controls and 153 neurological patients. The algorithm utilized a formant tracker in combination with a phoneme recognizer and subsequent signal processing analysis.
RESULTS
Articulatory undershoot of vowels was presented in a broad spectrum of progressive neurodegenerative diseases, including Parkinson's disease, progressive supranuclear palsy, multiple-system atrophy, Huntington's disease, essential tremor, cerebellar ataxia, multiple sclerosis, and amyotrophic lateral sclerosis, as well as in related dysarthria subtypes including hypokinetic, hyperkinetic, ataxic, spastic, flaccid, and their mixed variants. Formant ratios showed a higher sensitivity to vowel deficits than vowel space area. First formants of corner vowels were significantly lower for multiple-system atrophy than cerebellar ataxia. Second formants of vowels /a/ and /i/ were lower in ataxic compared to spastic dysarthria. Discriminant analysis showed a classification score of up to 41.0% for disease type, 39.3% for dysarthria type, and 49.2% for dysarthria severity. Algorithm accuracy reached an F-score of 0.77.
CONCLUSIONS
Distinctive vowel articulation alterations reflect underlying pathophysiology in neurological diseases. Objective acoustic analysis of vowel articulation has the potential to provide a universal method to screen motor speech disorders.
SUPPLEMENTAL MATERIAL
https://doi.org/10.23641/asha.23681529.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology |
UniBE Contributor: |
Rusz, Jan |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1558-9102 |
Publisher: |
American Speech-Language-Hearing Association |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
28 Jul 2023 12:39 |
Last Modified: |
04 Aug 2023 00:19 |
Publisher DOI: |
10.1044/2023_JSLHR-22-00526 |
PubMed ID: |
37499137 |
URI: |
https://boris.unibe.ch/id/eprint/185097 |
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