About
Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition
Benchmarks
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Subtasks
Datasets
Greatest papers with code
Speech Emotion Recognition with Multiscale Area Attention and Data Augmentation
In this paper, we apply multiscale area attention in a deep convolutional neural network to attend emotional characteristics with varied granularities and therefore the classifier can benefit from an ensemble of attentions with different scales.
audino: A Modern Annotation Tool for Audio and Speech
The tool allows audio data to be uploaded and assigned to a user through a key-based API.
ACTION DETECTION ACTIVITY DETECTION EMOTION RECOGNITION SPEAKER IDENTIFICATION SPEECH RECOGNITION
COSMIC: COmmonSense knowledge for eMotion Identification in Conversations
In this paper, we address the task of utterance level emotion recognition in conversations using commonsense knowledge.
Ranked #1 on
Emotion Recognition in Conversation
on EmoryNLP
Conversational Transfer Learning for Emotion Recognition
We propose an approach, TL-ERC, where we pre-train a hierarchical dialogue model on multi-turn conversations (source) and then transfer its parameters to a conversational emotion classifier (target).
Ranked #6 on
Emotion Recognition in Conversation
on DailyDialog
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation
IJCNLP 2019
• SenticNet/conv-emotion
• 
Emotion recognition in conversation (ERC) has received much attention, lately, from researchers due to its potential widespread applications in diverse areas, such as health-care, education, and human resources.
Ranked #1 on
Emotion Recognition in Conversation
on SEMAINE
Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
Emotion is intrinsic to humans and consequently emotion understanding is a key part of human-like artificial intelligence (AI).
Ranked #5 on
Emotion Recognition in Conversation
on EC
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection
EMNLP 2018
• SenticNet/conv-emotion
•
Emotion recognition in conversations is crucial for building empathetic machines.
Ranked #3 on
Emotion Recognition in Conversation
on SEMAINE
EMOTION RECOGNITION IN CONVERSATION MULTIMODAL EMOTION RECOGNITION
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
NAACL 2018
• SenticNet/conv-emotion
•
Emotion recognition in conversations is crucial for the development of empathetic machines.
Ranked #5 on
Emotion Recognition in Conversation
on SEMAINE
Speech SIMCLR: Combining Contrastive and Reconstruction Objective for Self-supervised Speech Representation Learning
Self-supervised visual pretraining has shown significant progress recently.
REPRESENTATION LEARNING SPEECH EMOTION RECOGNITION SPEECH RECOGNITION
ExpNet: Landmark-Free, Deep, 3D Facial Expressions
Our ExpNet CNN is applied directly to the intensities of a face image and regresses a 29D vector of 3D expression coefficients.
Ranked #1 on
3D Facial Expression Recognition
on 2017_test set
(using extra training data)
3D FACIAL EXPRESSION RECOGNITION EMOTION RECOGNITION FACIAL LANDMARK DETECTION