Abstract
Purpose: Interventions for speech disorders aim to produce changes that are not only acoustically measurable or perceptible to trained professionals but are also apparent to naive listeners. Due to challenges associated with obtaining ratings from suitably large listener samples, however, few studies currently evaluate speech interventions by this criterion. Online crowdsourcing technologies could enhance the measurement of intervention effects by making it easier to obtain real-world listeners’ ratings.Method: Stimuli, drawn from a published study by Sapir et al. (“Effects of intensive voice treatment (Lee Silverman Voice Treatment [LSVT]) on vowel articulation in dysarthric individuals with idiopathic Parkinson disease: Acoustic and perceptual findings” in Journal of Speech, Language, and Hearing Research, 50(4), 2007), were words produced by individuals who received intensive treatment (LSVT LOUD) for hypokinetic dysarthria secondary to Parkinson’s disease. Thirty-six online naive listeners heard randomly ordered pairs of words elicited pre- and posttreatment and reported which they perceived as “more clearly articulated.”Results: Mixed-effects logistic regression indicated that words elicited posttreatment were significantly more likely to be rated “more clear.” Across individuals, acoustically measured magnitude of change was significantly correlated with pre–post difference in listener ratings. Conclusions: These results partly replicate the findings of Sapir et al. (2007) and demonstrate that their acoustically measured changes are detectable by everyday listeners. This supports the viability of using crowdsourcing to obtain more functionally relevant measures of change in clinical speech samples.Supplemental Material S1. Token-level measurements of F1 and F2, as well as subject-level measurements of F2i/F2u ratio, both before and after treatment. Contains no identifiers.Supplemental Material S2. Results of perceptual ratings obtained from AMT listeners. Contains no identifiers.Supplemental Material S3. The analyses and results reported in this study can be reproduced by following the below steps: (1) Place this .Rmd file and the above-listed data files in the same directory; (2) Open the .Rmd file using RStudio; (3) Set the Working Directory to the directory in (1) above; (4) Use the “Knit” command to generate an output document.Nightingale, C., Swartz, M., Ramig, L. O., & McAllister, T. (2020). Using crowdsourced listeners’ ratings to measure speech changes in hypokinetic dysarthria: A proof-of-concept study. American Journal of Speech-Language Pathology. Advance online publication. https://doi.org/10.1044/2019_AJSLP-19-00162