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.
The DAIC-WOZ dataset is a valuable resource for researchers working on psychological distress conditions. This repository provides tools and code for extracting features at the question level, which can help in understanding the role of multimodal features in diagnosing depression. The related paper provides further insights into the methodology and results.
The Weibo User Depression Detection Dataset is a large-scale dataset for detecting depression in Weibo users. It includes user profiles, tweets, and labels indicating whether the user is depressed. The dataset is useful for researchers working on mental health and social media analysis.
Psy-Insight is a bilingual, interpretable multi-turn dataset for mental health counseling dialogues. It includes 6,208 rounds of multi-turn counseling dialogues in English and 5,776 rounds in Chinese, annotated with step-by-step reasoning labels and multi-task labels. This dataset is designed to support the application of large language models in mental health and is suitable for tasks such as emotion classification and psychological treatment interpretation.
The ToM QA Dataset is designed to evaluate question-answering models' ability to reason about beliefs. It includes 3 task types and 4 question types, creating 12 total scenarios. The dataset is inspired by theory-of-mind experiments in developmental psychology and is used to test models' understanding of beliefs and inconsistent states of the world.