ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP
Chengyun Deng, Shuzhong Lai, Chi Zhou, Mengyi Bao, Jingwen Yan,, Haifeng Li, Lin Yao, and Yueming Wang

TL;DR
ASD-Chat is a novel AI-powered dialogue system based on VB-MAPP and ChatGPT, designed to provide personalized social interventions for children with autism, addressing resource scarcity and clinical relevance.
Contribution
The paper introduces ASD-Chat, integrating VB-MAPP with ChatGPT to create a personalized, clinically grounded dialogue intervention system for ASD children.
Findings
Achieves intervention effects comparable to professional therapists
Addresses resource scarcity in ASD interventions
Demonstrates potential for long-term healthcare applications
Abstract
Early diagnosis and professional intervention can help children with autism spectrum disorder (ASD) return to normal life. However, the scarcity and imbalance of professional medical resources currently prevent many autistic children from receiving the necessary diagnosis and intervention. Therefore, numerous paradigms have been proposed that use computer technology to assist or independently conduct ASD interventions, with the aim of alleviating the aforementioned problem. However, these paradigms often lack a foundation in clinical intervention methods and suffer from a lack of personalization. Addressing these concerns, we propose ASD-Chat, a social intervention system based on VB-MAPP (Verbal Behavior Milestones Assessment and Placement Program) and powered by ChatGPT as the backbone for dialogue generation. Specifically, we designed intervention paradigms and prompts based on the…
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Taxonomy
TopicsAutism Spectrum Disorder Research · Assistive Technology in Communication and Mobility · Family and Disability Support Research
