SoulChat2.0: Psychological Counselor's Digital Twin Framework
SoulChat2.0 is a framework for constructing the digital twin of psychological counselors, designed to support the development of AI applications in mental health. It includes a data generation module and a modeling module, enabling the creation of personalized counseling models based on limited real-world counseling cases.
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SoulChat2.0 is a significant advancement in the field of mental health AI, offering a novel approach to building digital twins of psychological counselors. The framework leverages advanced LLMs to generate high-quality synthetic data that captures the language style and therapeutic techniques of specific counselors. This data is then used to fine-tune models, resulting in AI systems that can provide personalized and effective counseling support.
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Chinese Psychological QA DataSet - GitHub Repository
The Chinese Psychological QA DataSet is a collection of 102,845 community Q&A pairs related to psychological topics., providing a rich source of data for research and development in psychological counseling and AI applications. Each entry includes detailed question and answer information, making it a valuable resource for understanding user queries and generating appropriate responses.
Question-Level Feature Extraction on DAIC-WOZ Dataset
The DAIC-WOZ dataset contains clinical interviews designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder. This repository provides code for extracting question-level features from the DAIC-WOZ dataset, which can be used for multimodal analysis of depression levels.
CaiTI_dataset: Cognitive Behavioral Therapy Dataset - GitHub Repository
The CaiTI_dataset repository contains datasets for Motivational Interviewing and Cognitive Behavioral Therapy, curated by therapists to train CaiTI.