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

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 <i>QuickPic AAC</i>, an AI-driven application designed to generate topic-specific displays from photographs in a "just-in-time" manner. Using <i>QuickPic AAC</i>, 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 <i>QuickPic AAC</i>; percentage of vocabulary modified); and to (b) evaluate perceived usability of <i>QuickPic AAC</i> 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 <i>QuickPic AAC</i> application. These results support continued study of the implementation of <i>QuickPic AAC</i> in clinical practice and demonstrate the possibility of utilizing topic-specific displays as just-in-time supports.