EconPapers    
Economics at your fingertips  
 

QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking

Christina Yu (), Ralf W. Schlosser, Maurício Fontana de Vargas, Leigh Anne White, Rajinder Koul and Howard C. Shane
Additional contact information
Christina Yu: Boston Children’s Hospital, Waltham, MA 02453, USA
Ralf W. Schlosser: Boston Children’s Hospital, Waltham, MA 02453, USA
Maurício Fontana de Vargas: School of Information Studies, McGill University, Montreal, QC H3A 0G4, Canada
Leigh Anne White: Boston Children’s Hospital, Waltham, MA 02453, USA
Rajinder Koul: Department of Speech, Language, and Hearing Sciences, University of Texas at Austin, Austin, TX 78712, USA
Howard C. Shane: Boston Children’s Hospital, Waltham, MA 02453, USA

IJERPH, 2024, vol. 21, issue 9, 1-26

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: artificial intelligence; augmentative and alternative communication; AI; AAC; application; just-in-time; speech–language pathology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/21/9/1150/pdf (application/pdf)
https://www.mdpi.com/1660-4601/21/9/1150/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:21:y:2024:i:9:p:1150-:d:1467290

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jijerp:v:21:y:2024:i:9:p:1150-:d:1467290