Popular GitHub Repositories for Emotion Recognizer

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

EmotiVoice ?: a Multi-Voice and Prompt-Controlled TTS Engine

Multilingual Voice Understanding Model

Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition

?STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.

DELTA is a deep learning based natural language and speech processing platform. LF AI & DATA Projects: https://lfaidata.foundation/projects/delta/

State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.

This repo contains implementation of different architectures for emotion recognition in conversations.

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

? A list of accessible speech corpora for ASR, TTS, and other Speech Technologies

Real time emotion recognition

TensorFlow 101: Introduction to Deep Learning

A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

?A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc

Winner of Mozilla's $50,000 prize for AI

Emotion recognition using DNN with tensorflow

Official repository accompanying a CVPR 2022 paper EMOCA: Emotion Driven Monocular Face Capture And Animation. EMOCA takes a single image of a face as input and produces a 3D reconstruction. EMOCA sets the new standard on reconstructing highly emotional images in-the-wild

:book: 收集NLP领域相关的数据集、论文、开源实现，尤其是情感分析、情绪原因识别、评价对象和评价词抽取方面。