Preclinical Dialogue Simulation: Evaluating Response Accessibility in Conversational Artificial Intelligence for Aphasia Therapy.

Purpose: Large language model (LLM)-driven conversational agents are increasingly considered for use in clinical contexts, yet systematic approaches for evaluating their behavior in impairment-rich, speech-based therapeutic interactions remain limited. This study extends the Agent-Based Conversation...

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Detalles Bibliográficos
Publicado en:	Journal of Speech, Language & Hearing Research Vol. 69; no. 8; pp. 3781 - 3797
Autores principales:	Imaezue, Gerald C., Maram, Krishna V., Ajayi, David, Alohali, Isra, Butta, Rajesh K.
Formato:	Artículo
Publicado:	American Speech-Language-Hearing Association Aug2026
Materias:	Artificial intelligence Readability (Literary style) Communicative disorders Communication devices for people with disabilities Statistical models Rehabilitation of aphasic persons Benchmarking (Management) Research evaluation Natural language processing Speech-language pathology Simulation methods in education Data analysis software Speech therapy Regression analysis Sensitivity & specificity (Statistics)
Acceso en línea:	Ver este registro en EBSCOhost