HeartLink is an empathetic psychological model that uses a large language model fine-tuned on a large empathetic Q&A dataset. It can perceive users' emotions and experiences during conversations and provide empathetic responses using rich psychological knowledge, aiming to understand, comfort, and support users. The responses include emoji expressions to bridge the gap with users, offering psychological support and help during consultations.
The HeartLink project is based on the InternLM2-Chat model and has been fine-tuned to achieve empathetic functionality. The project supports text-to-speech synthesis and digital human display, and provides user emotion chart analysis. The project is under continuous development, and contributions through Star, PR, and Issue are welcome. The HeartLink psychological empathy question-and-answer dataset is derived from real psychological counseling scenarios. The first version uses about 180k rounds of question-and-answer pairs. The data covers a wide range of scenarios, including love, marriage, workplace, life, society, learning, sex, past, emotions, education, counseling, crisis, and many other rich scenarios.
The iBVP dataset is a collection of synchronized RGB and thermal infrared videos with PPG ground-truth signals acquired from an ear. It includes manual signal quality labels and dense signal-quality assessment using the SQA-PhysMD model. The dataset is designed to induce real-world variations in psycho-physiological states and head movement.
Lingxin (SoulChat) is a psychological health large model fine-tuned with millions of Chinese long-text instructions and multi-turn empathetic dialogue data in the field of psychological counseling.
This dataset contains survey responses from individuals in the tech industry about their mental health, including questions about treatment, workplace resources, and attitudes towards discussing mental health in the workplace. By analyzing this dataset, we can better understand how prevalent mental health issues are among those who work in the tech sector—and what kinds of resources they rely upon to find help—so that more can be done to create a healthier working environment for all.