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ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP

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arxiv 2409.01867 v1 pith:3SRCYSUX submitted 2024-09-03 cs.HC

classification cs.HC
keywords interventionchildrendialogueinterventionsparadigmsprofessionalsystemvb-mapp
verification ladder T0 review T1 audit T2 compute T3 formal
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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 clinical intervention method VB-MAPP and utilized ChatGPT's generative capabilities to facilitate social dialogue interventions. Experimental results demonstrate that our proposed system achieves competitive intervention effects to those of professional interventionists, making it a promising tool for long-term interventions in real healthcare scenario in the future.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Towards Emotion Co-regulation with LLM-powered Socially Assistive Robots: Integrating LLM Prompts and Robotic Behaviors to Support Parent-Neurodivergent Child Dyads

    cs.HC 2025-07 conditional novelty 6.0 of 10

    An LLM-driven MiRo-E robot coached parents and neurodivergent children through stressful LEGO tasks, and a two-dyad qualitative pilot suggested it can support emotion co-regulation.

  2. Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review

    cs.AI 2025-10 conditional novelty 1.0 of 10

    This paper is a survey: it organizes existing foundation-model work in neuroscience into five application domains and lists public datasets, without presenting new experiments.

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