ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912013447331840 |
|---|---|
| author | Deng, Chengyun Lai, Shuzhong Zhou, Chi Bao, Mengyi Yan, Jingwen Li, Haifeng Yao, Lin Wang, Yueming |
| author_facet | Deng, Chengyun Lai, Shuzhong Zhou, Chi Bao, Mengyi Yan, Jingwen Li, Haifeng Yao, Lin Wang, Yueming |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_01867 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP Deng, Chengyun Lai, Shuzhong Zhou, Chi Bao, Mengyi Yan, Jingwen Li, Haifeng Yao, Lin Wang, Yueming Human-Computer Interaction 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. |
| title | ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2409.01867 |