Click here to download project base paper of CHATGPT For mental health Support .
Abstract:
There has been an increasing research interest in deep learning projects developing specialized dialogue systems that can offer mental health support. However, gathering large-scale and real-life multi-turn conversations for mental and health support poses challenges due to the sensitivity of personal information,as well as the time and cost involved. To address these issues, we introduce the SMILE approach, an inclusive language expansion technique that employs ChatGPT to extend public single-turn dialogues into multi-turn ones. Our research first presents a preliminary exploratory study that validates the effectiveness of the SMILE approach. Furthermore, we conduct a comprehensive and systematic contrastive analysis of datasets generated with and without the SMILE approach, demonstrating that the SMILE method results in a large-scale, diverse, and close-to-real-life multi-turn health support conversation corpus, including dialogue topics, lexical and semantic features. Finally, we use the collected corpus (SMILECHAT) to develop a more effective dialogue system that offers emotional support and constructive suggestions in multi-turn conversations for health support. An alternative is crawling QA (Sunetal., 2021) on public health for undertraining psychological support models. However, single-turn conversations may not be sufficient for resolving health issues,a multiple-interaction
