Emotion detection involves identifying and classifying emotions expressed in textual data. It combines techniques from Natural Language Processing (NLP) and Machine Learning (ML) to analyze and interpret human emotions, which can be applied in various domains like customer service, social media analysis, and mental health monitoring.

Files relevant for my bachelor thesis on different automatic emotion recognition approaches

Large-Scale Selfie Video Dataset (L-SVD): A Benchmark for Emotion Recognition

This repository is related to all about Machine Learning, Deep Learning, Computer Vision, NLP, and Research Projects

A hackathon project to use a realtime feed of in-ear EEG data from IDUN Guardian to analyze emotional state and control Spotify with it.

😎 Awesome lists about Speech Emotion Recognition

Example projects built with the Hume AI APIs

Files uploaded from the Raspberry Pi that uses emotional detection to prompt two outputs via the LCD screen and speaker. For more information, please read the README.md.

Fast emotion classification model

The project develops a facial emotion classifier using the k-Nearest Neighbors (kNN) algorithm. The classifier uses Histogram of Oriented Gradients (HOG) and Principal Component Analysis (PCA) for dimensionality reduction with usage of normalisaton, preprocessing and augmentation.

Official code repository for paper "Multi-modal Speech Emotion Recognition using Multi-head Attention Fusion of Multi-feature Embeddings". Paper accepted to EAI INISCOM 2023

Code repository for paper: "The Face of Populism: Examining Differences in Facial Emotional Expressions of Political Leaders Using Machine Learning"

This repository houses a robust Emotion Analysis and Detection system designed to interpret and identify emotions from text. This project aims to provide accurate insights into human emotions, enabling applications in diverse fields including psychology, marketing, human-computer interaction, and sentiment analysis.

Repository for paper: "Dynamic Exploratory Graph Analysis of Emotions in Politics"

The AI-powered ser Python package is a tool for recognizing and analyzing emotions in speech. Employing state-of-the-art machine learning and audio processing techniques, it classifies emotions in audio recordings, extracts transcripts, and integrates these with a timeline of emotional states

This small library adds face and emotion analysis to any website, with less than 1 MB, and is fully GDPR-compliant.

The detection of emotion is made by using the machine learning concept. You can use the trained dataset to detect the emotion of the human being. For detecting the different emotions, first, you need to train those different emotions, or you can use a dataset already available on the internet.

A modern GUI Based Face Recognition and Emotion Predictor using Machine Learning

Project Babble Module for VRCFaceTracking v5. An open-source VR mouth tracking solution