audio-text multimodal emotion recognition model which is robust to missing data

A Unimodal Valence-Arousal Driven Contrastive Learning Framework for Multimodal Multi-Label Emotion Recognition (ACM MM 2024 oral)

Cognitive Robotics University Exam Project

Published in Springer Multimedia Tools and Applications Journal.

This emotion recognition app analyzes text, facial expressions, and speech to detect emotions. Designed for self-awareness and mental well-being, it provides personalized insights and recommendations.

[MM 2025] The official implementation code for "VAEmo: Efficient Representation Learning for Visual-Audio Emotion with Knowledge Injection“

A Tensorflow implementation of Speech Emotion Recognition using Audio signals and Text Data

This API utilizes a pre-trained model for emotion recognition from audio files. It accepts audio files as input, processes them using the pre-trained model, and returns the predicted emotion along with the confidence score. The API leverages the FastAPI framework for easy development and deployment.

All experiments were done to classify multimodal data.

SERVER: Multi-modal Speech Emotion Recognition using Transformer-based and Vision-based Embeddings

Emotion recognition from Speech & Text using different heterogeneous ensemble learning methods

A survey of deep multimodal emotion recognition.

This repository provides the codes for MMA-DFER: multimodal (audiovisual) emotion recognition method. This is an official implementation for the paper MMA-DFER: MultiModal Adaptation of unimodal models for Dynamic Facial Expression Recognition in-the-wild.

😎 Awesome lists about Speech Emotion Recognition

Scientific Reports - Open access - Published: 14 February 2025

🚀 Pre-process, annotate, evaluate, and train your Affect Computing (e.g., Multimodal Emotion Recognition, Sentiment Analysis) datasets ALL within MER-Factory! (LangGraph Based Agent Workflow)

Offical implementation of paper "MSAF: Multimodal Split Attention Fusion"

The code for our INTERSPEECH 2020 paper - Jointly Fine-Tuning "BERT-like'" Self Supervised Models to Improve Multimodal Speech Emotion Recognition

The code for our IEEE ACCESS (2020) paper Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature Fusion.

The repo contains an audio emotion detection model, facial emotion detection model, and a model that combines both these models to predict emotions from a video