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.
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.
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.
MentalManip数据集是由Wang等人(2024b)引入的,专门用于检测和分类心理操纵的对话数据集。该数据集包含4000个多轮虚构对话,来源于在线电影剧本,并进行了多层次的标注,包括操纵的存在、操纵技巧和目标脆弱性。数据集的创建旨在通过高质量的标注确保数据的一致性和准确性,从而支持心理操纵检测的研究。
This paper discusses Helply - a synthesized ML training dataset focused on psychology and therapy, created by Alex Scott and published by NamelessAI. The dataset developed by Alex Scott is a comprehensive collection of synthesized data designed to train LLMs in understanding psychological and therapeutic contexts. This dataset aims to simulate real-world interactions between therapists and patients, enabling ML models to learn from a wide range of scenarios and therapeutic techniques.