Understanding Human Communication Patterns with LLMs: A Study of Short Conversations in Autistic Children
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Automated systems that analyze short conversation samples could offer valuable insights into autistic children's real-world social communication competence while highlighting opportunities for growth. In this study, we explore the potential of using large language models (LLMs) to assess social interaction quality during casual conversations that include autistic youth. We focus on evaluating the ability of LLMs to predict conversation quality, with the long-term goal of informing tailored communication support strategies that promote optimal social outcomes. Results underscore the need for caution when using LLMs to inform clinical decision-making in autism.
