A multidimensional examination of vowel-related articulatory deficits in Parkinson’s disease

Abstract

Purpose: This study aimed to investigate the perceptual, acoustic, and kinematic differences between speakers with and without dysarthria due to Parkinson’s disease (PD) across conversational, less clear, and more clear clarity conditions.Methods: Forty participants, including 22 with PD and 18 controls, read three phrases aloud using conversational, less clear, and more clear speaking conditions. Acoustic and kinematic measures were obtained from the diphthong /aɪ/ and selected vowels in the sentences. A total of 368 listeners from crowdsourcing provided ratings for intelligibility and articulatory precision. Linear mixed-effects models were employed to examine (1) baseline conversational speaker group differences for perceptual, acoustic, and kinematic measures, and (2) clarity-related changes across the selected measures.Results: In the baseline conversational condition, speakers with PD were perceived as less intelligible and precise. However, none of the acoustic or kinematic measures differed between the speakers with and without PD. When asked to modify clarity, both speaker groups successfully modified various acoustic and kinematic measures, resulting in perceptual changes in intelligibility and articulatory precision. However, speakers with PD showed a reduced magnitude of change compared to HC speakers.Conclusions: The findings generally support the efficacy of clear speech as a behavioral treatment cue. However, the findings also highlight a large variability in strategies employed by speakers to modify their speech clarity.

The Effects of Electromagnetic Articulography Sensors on Speech in Individuals With and Without Dysarthria

“…However, relying solely on acoustic signals to infer articulatory gestures is complicated by the fact that multiple articulatory gestures can produce the same acoustic signal (Brunner & Hoole, 2012;Hughes & Abbs, 1976;Perkell et al, 1993;Perrier & Fuchs, 2015). Thus, kinematic analyses using EMA to quantify articulatory working space (Lee et al, 2017;Thompson & Kim, 2024a, 2024b, tongue displacement and speed (Mefferd, 2015;Rong et al, 2012), and movement variability (Chu et al, 2020) are particularly beneficial for studying speakers with and without speech disorders, such as dysarthria.…”