Vowel Acoustics as Predictors of Speech Intelligibility in Dysarthria

Purpose: This study sought to determine if alternative vowel space area (VSA) measures (i.e., novel trajectory-based measures: vowel space hull area and vowel space density) predicted speech intelligibility to the same extent as two traditional vowel measures (i.e., token-based measures: VSA and corner dispersion) in speakers with dysarthria. Additionally, this study examined if the strength of the relationship between acoustic vowel measures and intelligibility differed based on how intelligibility was measured (i.e., orthographic transcriptions [OTs] and visual analog scale [VAS] ratings). Method: The Grandfather Passage was read aloud by 40 speakers with dysarthria of varying etiologies, including Parkinson's disease (n = 10), amyotrophic lateral sclerosis (n = 10), Huntington's disease (n = 10), and cerebellar ataxia (n = 10). Token- and trajectory-based acoustic vowel measures were calculated from the passage. Naive listeners (N = 140) were recruited via crowdsourcing to provide OTs and VAS intelligibility ratings. Hierarchical linear regression models were created to model OTs and VAS intelligibility ratings using the acoustic vowel measures as predictors. Results: Traditional VSA was the sole significant predictor of speech intelligibility for both the OTs (R-2 = .259) and VAS (R-2 = .236) models. In contrast, the trajectory-based measures were not significant predictors of intelligibility. Additionally, the OTs and VAS intelligibility ratings conveyed similar information. Conclusions: The findings suggest that traditional token-based vowel measures better predict intelligibility than trajectory-based measures. Additionally, the findings suggest that VAS methods are comparable to OT methods for estimating speech intelligibility for research purposes.