{"id":34930,"url":"https://github.com/eric-erki/awesome-affective-computing","name":"awesome-affective-computing","description":"A curated list of awesome affective computing papers, software, open-source projects, and resources","projects_count":54,"last_synced_at":"2026-06-05T18:00:30.851Z","repository":{"id":99090860,"uuid":"145287447","full_name":"eric-erki/awesome-affective-computing","owner":"eric-erki","description":"A curated list of awesome affective computing papers, software, open-source projects, and 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align=center\u003e Awesome Affective Computing \u003c/h1\u003e\n\n\u003cdiv align=\"center\"\u003e\n\t\u003cimg width=\"900\" src=\"awesome-affective-computing.png\" alt=\"Awesome Affective Computing\"\u003e\n\u003c/div\u003e\n\n\u003cp align=\"center\"\u003e\n\t\u003ca href=\"https://github.com/sindresorhus/awesome\"\u003e\n\t\t\u003cimg alt=\"Awesome\" src=\"https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg\"\u003e\n\t\u003c/a\u003e\n\t\u003ca href=\"https://twitter.com/intent/tweet?text=Awesome%20Affective%20Computing%20-%20A%20curated%20list%20of%20awesome%20affective%20computing%20papers,%20software,%20and%20resources%20by%20@AmrMKayid\u0026url=https://github.com/AmrMKayid/awesome-affective-computing\u0026hashtags=affective_computing,emotion_recognition,emotionalintelligence,artificialintelligence,deeplearning\"\u003e\n\t\t\u003cimg alt=\"tweet\" src=\"https://img.shields.io/twitter/url/http/shields.io.svg?style=social\"\u003e\n\t\u003c/a\u003e\n\u003c/p\u003e\n\n\n\n# Contents\n\n- [Papers](#papers)\n\t- [General](#general) | [Facial](#facial) | [Voice](#voice) | [Behavioral](#behavioral)\n- [Software](#software)\n- [Courses](#courses)\n- [Books](#books)\n- [Open-Source Projects](#projects)\n\n\n# Papers\n\n## General\n\n- [Affective Computing](https://affect.media.mit.edu/pdfs/95.picard.pdf)\n- [Theories, Methods and Current Research on Emotions](https://irenelopatovska.files.wordpress.com/2012/10/lopatovska_arapakis_2011_theories.pdf)\n- [Analysis of emotion recognition using facial expressions, speech and multimodal information](https://dl.acm.org/citation.cfm?id=1027968)\n- [An Emotion Recognition System for Mobile Applications](https://ieeexplore.ieee.org/document/7862118/)\n\n\n## Facial\n- [A comprehensive study on Facial Expressions Recognition Techniques](https://ieeexplore.ieee.org/document/7508167/)\n- [Recognizing Facial Expressions Using Deep Learning](http://cs231n.stanford.edu/reports/2017/pdfs/224.pdf)\n- [Deep learning for facial expression recognition: A step closer to a smartphone that knows your moods](https://ieeexplore.ieee.org/document/7889290/)\n- [Deep learning for real-time robust facial expression recognition on a smartphone](https://ieeexplore.ieee.org/abstract/document/6776135/)\n- [Automatic Facial Feature Extraction and Expression Recognition based on Neural Network](https://arxiv.org/pdf/1204.2073.pdf)\n- [Automatic facial expression recognition based on a deep convolutional-neural-network structure](https://ieeexplore.ieee.org/abstract/document/7965717/)\n- [AU-aware Deep Networks For Facial Expression Recognition](http://www.jdl.ac.cn/doc/2011/20141317351319923_2013_fg_myliu_au-aware%20deep%20networks%20for%20facial%20expression%20recognition.pdf)\n- [An Emotion Recognition Model Based on Facial Recognition in Virtual Learning Environment](https://ac.els-cdn.com/S1877050917327679/1-s2.0-S1877050917327679-main.pdf?_tid=dfa912d0-4d1d-46c9-8047-e704fa20031d\u0026acdnat=1530789316_10496a5c00e6542ade37b5d1362acdda)\n- [A Brief Review of Facial Emotion Recognition Based on Visual Information](http://www.mdpi.com/1424-8220/18/2/401)\n- [Facial Expression Recognition via a Boosted Deep Belief Network](https://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Liu_Facial_Expression_Recognition_2014_CVPR_paper.pdf)\n- [Image based Static Facial Expression Recognition with Multiple Deep Network Learning](https://dl.acm.org/citation.cfm?id=2830595)\n- [Facial Expression Emotion Detection for Real-Time Embedded Systems](http://www.mdpi.com/2227-7080/6/1/17/)\n- [Facial emotion recognition in continuous video](https://www.researchgate.net/publication/259891535_Facial_emotion_recognition_in_continuous_video)\n- [An Efficient Method to Face and Emotion Detection](https://ieeexplore.ieee.org/document/7279967/)\n- [A Novel Feature Extraction Technique for Facial Expression\nRecognition](https://pdfs.semanticscholar.org/d6c7/092111a8619ed7a6b01b00c5f75949f137bf.pdf)\n- [Emotion Recognition from Arbitrary View Facial Images](http://www.cis.pku.edu.cn/faculty/vision/zlin/Publications/2010-ECCV-Emotion.pdf)\n\n\n## Voice\n\n- [EmoVoice — A framework for online recognition of emotions from voice](https://www.informatik.uni-augsburg.de/lehrstuehle/hcm/publications/2008-PIT-Vogt/Vogtetal-PIT08.pdf)\n- [EmoVoice: a System to Generate Emotions in Speech](https://www.researchgate.net/publication/221478213_Emovoice_a_system_to_generate_emotions_in_speech)\n- [Speech Emotion Recognition](https://pdfs.semanticscholar.org/8b09/af0774f1d5985fb86cdda4ad33c58608a1e6.pdf)\n- [Speech Emotion Recognition Using Support Vector Machine](http://www.earticle.net/Article.aspx?sn=204547)\n- [Speech emotion recognition using hidden Markov models](https://www.sciencedirect.com/science/article/pii/S0167639303000992)\n- [Emotion Recognition From Speech With Recurrent Neural Networks](https://arxiv.org/abs/1701.08071)\n- [Speech Emotion Recognition Using Deep Neural Network and Extreme Learning Machine](https://www.microsoft.com/en-us/research/publication/speech-emotion-recognition-using-deep-neural-network-and-extreme-learning-machine/)\n- [Deep learning for robust feature generation in audiovisual emotion recognition](https://ieeexplore.ieee.org/document/6638346)\n\n\n## Behavioral\n\n- [Three-Dimensional, Kinematic, Human Behavioral Pattern-Based Features for Multimodal Emotion Recognition](http://www.mdpi.com/2414-4088/1/3/19)\n\n\n\n# Software\n\n- [Affectiva](https://www.affectiva.com/) - Affectiva develop software to recognize human emotions based on facial cues.\n- [Emotient](https://imotions.com/emotient/) - Emotient Facial Expression Analysis Engine\n- [EmoVu](http://www.eyeris.ai/) - EmoVu is a deep learning-based emotion recognition that reads facial micro-expressions in real-time\n- [Nviso](http://www.nviso.ch/technology.html) - NVISO detect and predict human behaviours using Visual Intelligence.\n- [Kairos](https://www.kairos.com/) - Serve Businesses with Face Recognition\n- [Cognitive-Emotion-Python](https://github.com/Microsoft/Cognitive-Emotion-Python), Python SDK for the Microsoft Emotion API, part of Cognitive Services\n\n\n\n# Courses\n\n- [MIT - Affective Computing](https://ocw.mit.edu/courses/media-arts-and-sciences/mas-630-affective-computing-fall-2015/)\n- [Knowledge-Based AI: Cognitive Systems](https://eg.udacity.com/course/knowledge-based-ai-cognitive-systems--ud409)\n- [Computer Vision Nanodegree](https://in.udacity.com/course/computer-vision-nanodegree--nd891)\n- [Coursera - Affective computing](https://www.coursera.org/lecture/emotions/affective-computing-gebqS)\n\n\n\n# Books\n\n- [Affective Computing](https://mitpress.mit.edu/books/affective-computing)\n- [Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence](https://www.amazon.com/Heart-Machine-Artificial-Emotional-Intelligence/dp/1628727330)\n- [The Oxford Handbook of Affective Computing](https://www.amazon.com/Handbook-Affective-Computing-Library-Psychology/dp/0199942234)\n- [Affective Computing and Sentiment Analysis](https://www.springer.com/gp/book/9789400717565)\n\n\n\n# Open-Source Projects\n\n- [emotion-recognition-neural-networks](https://github.com/isseu/emotion-recognition-neural-networks), Emotion recognition using DNN with tensorflow\n- [Emotion](https://github.com/petercunha/Emotion), Recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.\n- [EmotionRecognition](https://github.com/leonardean/EmotionRecognition), Real time emotion recogniser using web camera based on FACS.\n- [face_classification](https://github.com/oarriaga/face_classification), Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.\n- [Emotion-Recognition-RNN](https://github.com/saebrahimi/Emotion-Recognition-RNN), Recurrent Neural Networks for Emotion Recognition in Video\n- [EmotionNet](https://github.com/co60ca/EmotionNet), Convolutional Neural Network for Emotion Recognition\n- [emotion-conv-net](https://github.com/GautamShine/emotion-conv-net), Real-time emotion recognition using convolutional neural nets.\n- [DeepSentiment](https://github.com/vyassu/DeepSentiment), Speech Emotion Recognition using FFT and SVM\n- [Voice-Emotion-Detector](https://github.com/crhung/Voice-Emotion-Detector), Voice Emotion Detector that detects emotion from audio speech using one dimensional CNNs (convolutional neural networks) using keras and tensorflow on Jupyter Notebook.\n- [Speech-Emotion-Analyzer](https://github.com/MITESHPUTHRANNEU/Speech-Emotion-Analyzer), The neural network model is capable of detecting eight different male/female emotions from audio speeches. (Deep Learning, Python)\n- [Emotion_Recognition](https://github.com/miguelki/Emotion_Recognition)\n- [Emotion_Voice_Recognition_Chainer](https://github.com/SnowMasaya/Emotion_Voice_Recognition_Chainer-)\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/eric-erki%2Fawesome-affective-computing/projects"}