Ritabrata04 / Hybrid-Approach-To-Depression-DetectionLinks
This repository applies Deep Learning techniques for depression detection in text, using LSTM, GRU, BiLSTM, BERT models, and a baseline FFNN. It also includes data visualizations, autoencoder semantics, KMeans clustering, and detailed performance comparisons.
☆18Updated 2 years ago
Alternatives and similar repositories for Hybrid-Approach-To-Depression-Detection
Users that are interested in Hybrid-Approach-To-Depression-Detection are comparing it to the libraries listed below
Sorting:
- Official source code for the paper: "It’s Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers"☆60Updated 2 years ago
- The code for our IEEE ACCESS (2020) paper Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature Fusion.☆123Updated 4 years ago
- This repository provides implementation for the paper "Self-attention fusion for audiovisual emotion recognition with incomplete data".☆155Updated last year
- Official source code for the paper: "Reading Between the Frames Multi-Modal Non-Verbal Depression Detection in Videos"☆84Updated last year
- Detecting Anxiety and Depression using facial emotion recognition and speech emotion recognition. Written in pythonPython☆64Updated 4 years ago
- A demo for multi-modal emotion recognition.(多模态情感识别demo)☆91Updated last year
- This repository implements the Tensor Fusion Network (TFN) for multimodal sentiment analysis using the CMU-MOSI dataset. TFN integrates l…☆13Updated last year
- depression detection by using tweets☆27Updated 6 years ago
- Automatic Depression Detection: a GRU/ BiLSTM-based Model and An Emotional Audio-Textual Corpus☆200Updated 2 years ago
- ABAW6 (CVPR-W) We achieved second place in the valence arousal challenge of ABAW6☆30Updated last year
- Multimodal Fusion, Multimodal Sentiment Analysis☆26Updated 5 years ago
- MultiModal Sentiment Analysis architectures for CMU-MOSEI.☆54Updated 3 years ago
- A Fully End2End Multimodal System for Fast Yet Effective Video Emotion Recognition☆40Updated last year
- Multimodal sentiment analysis☆23Updated 2 years ago
- Detecting depressed Patient based on Speech Activity, Pauses in Speech and Using Deep learning Approach☆20Updated 3 years ago
- Automatic Depression Detection by Multi-model Ensemble. Based on DAIC-WOZ dataset.☆41Updated 5 years ago
- 多模态,语音和文本结合的情感识别,大模型finetune☆23Updated 2 years ago
- Codebase for EMNLP 2024 Findings Paper "Knowledge-Guided Dynamic Modality Attention Fusion Framework for Multimodal Sentiment Analysis"☆65Updated last year
- Bachelor Thesis - Deep Learning-based Multi-modal Depression Estimation☆78Updated 2 years ago
- Speech Emotion Classification with novel Parallel CNN-Transformer model built with PyTorch, plus thorough explanations of CNNs, Transform…☆261Updated 5 years ago
- The final coursework for AI in Mental Health @ PKU.☆18Updated 2 years ago
- Two-stage Temporal Modelling Framework for Video-based Depression Recognition using Graph Representation☆30Updated last year
- ☆22Updated last year
- MultiEMO: An Attention-Based Correlation-Aware Multimodal Fusion Framework for Emotion Recognition in Conversations (ACL 2023)☆90Updated 2 years ago
- Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed…☆97Updated 4 years ago
- Data parser for the CMU-MultimodalSDK package including parsing for CMU-MOSEI, CMU-MOSI, and POM datasets☆35Updated last year
- depression-detect Predicting depression from AVEC2014 using ResNet18.☆58Updated last year
- A baseline for Weibo User Depression Detection Dataset (WU3D)☆35Updated 3 years ago
- ☆17Updated 2 years ago
- Detecting depression in a conversation using Convolutional Neral Network☆74Updated 4 years ago