Version 1
: Received: 10 July 2024 / Approved: 11 July 2024 / Online: 15 July 2024 (15:38:29 CEST)
How to cite:
Yu, C.; Schlosser, R.; Fontana de Vargas, M.; White, L. A.; Koul, R.; Shane, H. QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking. Preprints2024, 2024070999. https://doi.org/10.20944/preprints202407.0999.v1
Yu, C.; Schlosser, R.; Fontana de Vargas, M.; White, L. A.; Koul, R.; Shane, H. QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking. Preprints 2024, 2024070999. https://doi.org/10.20944/preprints202407.0999.v1
Yu, C.; Schlosser, R.; Fontana de Vargas, M.; White, L. A.; Koul, R.; Shane, H. QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking. Preprints2024, 2024070999. https://doi.org/10.20944/preprints202407.0999.v1
APA Style
Yu, C., Schlosser, R., Fontana de Vargas, M., White, L. A., Koul, R., & Shane, H. (2024). <em>QuickPic AAC</em>: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking. Preprints. https://doi.org/10.20944/preprints202407.0999.v1
Chicago/Turabian Style
Yu, C., Rajinder Koul and Howard Shane. 2024 "<em>QuickPic AAC</em>: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking" Preprints. https://doi.org/10.20944/preprints202407.0999.v1
Abstract
As artificial intelligence (AI) makes significant headway in various arenas, the field of Speech-Language Pathology is at the precipice of experiencing a transformative shift towards automation. This study introduces QuickPic AAC, an AI-driven application designed to generate topic-specific displays from photographs in a "just-in-time" manner. Using QuickPic AAC, this study aimed to (a) determine which of two AI algorithms (NLG-AAC and GPT-3.5) results in greater specificity of vocabulary (i.e., percentage of vocabulary kept/deleted by clinician relative to vocabulary generated by QuickPic AAC; percentage of vocabulary modified); and to (b) evaluate perceived usability of QuickPic AAC among practicing speech-language pathologists. Results revealed that the GPT-3.5 algorithm consistently resulted in greater specificity of vocabulary and that speech-language pathologists expressed high user satisfaction for the QuickPic AAC application. These results support continued study of the implementation of QuickPic AAC in clinical practice and demonstrate the possibility of utilizing topic-specific displays as just-in-time supports.
Keywords
autism spectrum disorder (ASD); artificial intelligence (AI); augmentative and alternative communication (AAC); speech pathology; application; topic displays; just-in-time (JIT)
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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