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◆ International journal of language & communication disorders2026-01-01

User Experience and Satisfaction With a Web-Based Application to Improve Intelligibility in Parkinson's Disease.

Gemma Moya-Galé, Julia Hunter, Alireza Goudarzi, Edwin Maas, Leire Escalada-Cebadero

一句话结论 · In one sentence

Qualitative data yields preliminary support for the use of a digital speech web-based application that provides noise-augmented automatic speech recognition feedback to improve intelligibility in individuals with PD. Results support further testing of this protocol with a larger cohort of participants in a controlled environment.

原始摘要(英文原文)· Original abstract
BACKGROUND/OBJECTIVES: Motor speech impairments, such as hypokinetic dysarthria, are highly prevalent among individuals with Parkinson's disease (PD). These voice and speech deficits may significantly impact speech intelligibility, leading many individuals with PD to withdraw socially. Digital platforms may provide a feasible way to address motor speech impairments in this population while also fostering patients' self-management skills through independent home-based practice. The objective of this preliminary one-group pre-post treatment study is to provide a qualitative examination of participants' experience and satisfaction using a custom-developed web-based application to improve speech intelligibility using noise-augmented automatic speech recognition feedback. METHODS: Four individuals with PD completed one month (= 16 sessions) of a novel intensive speech treatment program through a web-based application with weekly online support from a speech-language pathologist. At post-treatment, participants completed individual interviews to document their user experience with the digital platform and a brief satisfaction survey. Interviews were analysed qualitatively following an experiential orientation and reflexive thematic analysis. RESULTS: Overall, participants were satisfied with their experience using the app. Four themes were generated from the data set: (1) From external feedback to metacognitive awareness, (2) two worlds colliding, (3) beyond voice and speech gains: Psychosocial benefits of noise-augmented automatic speech recognition, and (4) reconciling the demands of a digital interface with the motor and non-motor symptoms of Parkinson's disease. CONCLUSIONS: Qualitative data yields preliminary support for the use of a digital speech web-based application that provides noise-augmented automatic speech recognition feedback to improve intelligibility in individuals with PD. Results support further testing of this protocol with a larger cohort of participants in a controlled environment. WHAT THIS PAPER ADDS: What is already known on this subject Motor speech impairments, such as hypokinetic dysarthria, are highly prevalent among individuals with Parkinson's disease (PD). These voice and speech deficits may significantly impact speech intelligibility, leading many individuals with PD to withdraw socially. Digital platforms may provide a feasible way to address motor speech impairments in this population while also fostering patients' self-management skills through independent home-based practice. Digital tools for speech rehabilitation in this population are emerging in the field. However, no digital tool has explored the role of automatic speech recognition (ASR) in noise as a treatment method. Hence, user experience for this novel and naturalistic method warrants further investigation. What this study adds to the existing knowledge The objective of this one-group pre-post treatment study is to provide a qualitative examination of participants' experience and satisfaction using a custom-developed web-based application to improve speech intelligibility using noise-augmented ASR feedback. To the authors' knowledge, this is the first study to describe this novel approach, powered by artificial intelligence, and provide a qualitative examination of this naturalistic method targeting intelligibility. This information will guide future iterations of this web-based technology and provide preliminary insights into how noise-augmented ASR feedback can contribute to patient management. What are the clinical implications of this study? Patient-led digital technologies leveraging ASR in noise hold promise for clinical practice. For the participants with dysarthria secondary to PD in our study, a novel speech treatment that targets intelligibility through noise-augmented ASR feedback was deemed useful and promising to improve not only their voice and speech but also to increase their awareness of how dysarthria impacts their voice in noisy conditions. Additionally, some participants reported increases in confidence and motivation to communicate, which underscores a promising psychosocial impact of this approach.
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User Experience and Satisfaction With a Web-Based Application to Improve Intelligibility in Parkinson's Disease. — 科研速览 Science Skim