Crowdsourced Perceptual Ratings of Voice Quality in People With Parkinson's Disease Before and After Intensive Voice and Articulation Therapies: Secondary Outcome of a Randomized Controlled Trial

Author:

McAllister Tara1ORCID,Nightingale Christopher2,Moya-Galé Gemma3ORCID,Kawamura Ava4,Ramig Lorraine Olson5678

Affiliation:

1. New York University, NY

2. Gallaudet University, Washington, DC

3. Long Island University, Brooklyn, NY

4. Georgetown University, Washington, DC

5. University of Colorado Boulder

6. National Center for Voice and Speech, Denver, CO

7. Columbia University, New York, NY

8. LSVT Global, Inc., Tucson, AZ

Abstract

Purpose: Limited research has examined the suitability of crowdsourced ratings to measure treatment effects in speakers with Parkinson's disease (PD), particularly for constructs such as voice quality. This study obtained measures of reliability and validity for crowdsourced listeners' ratings of voice quality in speech samples from a published study. We also investigated whether aggregated listener ratings would replicate the original study's findings of treatment effects based on the Acoustic Voice Quality Index (AVQI) measure. Method: This study reports a secondary outcome measure of a randomized controlled trial with speakers with dysarthria associated with PD, including two active comparators (Lee Silverman Voice Treatment [LSVT LOUD] and LSVT ARTIC), an inactive comparator (untreated PD), and a healthy control group. Speech samples from three time points (pretreatment, posttreatment, and 6-month follow-up) were presented in random order for rating as “typical” or “atypical” with respect to voice quality. Untrained listeners were recruited through the Amazon Mechanical Turk crowdsourcing platform until each sample had at least 25 ratings. Results: Intrarater reliability for tokens presented repeatedly was substantial (Cohen's κ = .65–.70), and interrater agreement significantly exceeded chance level. There was a significant correlation of moderate magnitude between the AVQI and the proportion of listeners classifying a given sample as “typical.” Consistent with the original study, we found a significant interaction between group and time point, with the LSVT LOUD group alone showing significantly higher perceptually rated voice quality at posttreatment and follow-up relative to the pretreatment time point. Conclusions: These results suggest that crowdsourcing can be a valid means to evaluate clinical speech samples, even for less familiar constructs such as voice quality. The findings also replicate the results of the study by Moya-Galé et al. ( 2022 ) and support their functional relevance by demonstrating that the effects of treatment measured acoustically in that study are perceptually apparent to everyday listeners.

Publisher

American Speech Language Hearing Association

Subject

Speech and Hearing,Linguistics and Language,Language and Linguistics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. ¿Notas La Diferencia? [Do You Hear the Difference?]: Perceptual Consequences of Intensive Voice Treatment in Spanish Speakers With Parkinson's Disease;Journal of Speech, Language, and Hearing Research;2024-09-12

2. Towards an Interpretable Representation of Speaker Identity via Perceptual Voice Qualities;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Analysis of Voice in Parkinson’s Disease Utilizing the Acoustic Voice Quality Index;Journal of Voice;2024-01

4. Permod: Perceptually Grounded Voice Modification With Latent Diffusion Models;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16

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