ICASSP2022-Depression: Automatic Depression Detection
This repository provides code and data for automatic depression detection using a GRU/BiLSTM-based model. It includes an emotional audio-textual corpus designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder.
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The ICASSP2022-Depression project presents a comprehensive approach to automatic depression detection using deep learning techniques. The repository includes a GRU/BiLSTM-based model and an emotional audio-textual corpus, making it a valuable resource for researchers working on mental health and natural language processing.
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Mental Health Data at WHO
The World Health Organization (WHO) provides a comprehensive collection of global health data, including mental health statistics. This resource offers insights into various mental health conditions and their prevalence, helping researchers and policymakers understand and address mental health challenges worldwide.
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.
Psych-101: Human Psychological Experiment Transcripts Dataset
Psych-101 is a dataset of natural language transcripts from human psychological experiments, comprising trial-by-trial data from 160 experiments and 60,092 participants, making 10,681,650 choices. It provides valuable insights into human decision-making processes and is available under the Apache License 2.0.