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S1_JSLHR-22-00526illner.pdf (1.35 MB)

Vowel articulation in dysarthrias (Illner et al., 2023)

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posted on 2023-07-27, 19:16 authored by Vojtech Illner, Tereza Tykalova, Dominik Skrabal, Jiri Klempir, Jan Rusz

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 S1. A detailed description of the results based on reading passage.

Illner, V., Tykalova, T., Skrabal, D., Klempir, J., & Rusz, J. (2023). Automated vowel articulation analysis in connected speech among progressive neurological diseases, dysarthria types, and dysarthria severities. Journal of Speech, Language, and Hearing Research, 66(8), 2600–2621. https://doi.org/10.1044/2023_JSLHR-22-00526

Funding

This study was supported by the Czech Ministry of Health (Grants MH CZ-DRO-VFN64165 to Jiri Klempir and Jan Rusz and NU-20-08-00445 to Vojtech Illner, Tereza Tykalova, Dominik Skrabal, and Jan Rusz), National Institute for Neurological Research (Programme EXCELES; ID Project No. LX22NPO5107), funded by the European Union–Next Generation EU to Tereza Tykalova and Jan Rusz, Czech Technical University in Prague (Grant SGS23/170/OHK3/3 T/13 to Vojtech Illner), and by the Cooperation Program, research area Neuroscience to Jiri Klempir and Jan Rusz.

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