Emotion Recognition
200 papers with code • 5 benchmarks • 26 datasets
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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Datasets
Aff-Wild
Hateful Memes
Aff-Wild2
SEED
EmotionLines
ISEAR
ExpW
CARER
Subtasks
Greatest papers with code
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond
Our approach only needs to modify the input image and can work with any network to improve its performance.
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.
COSMIC: COmmonSense knowledge for eMotion Identification in Conversations
declare-lab/conv-emotion
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Findings of the Association for Computational Linguistics 2020
In this paper, we address the task of utterance level emotion recognition in conversations using commonsense knowledge.
Ranked #3 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 #13 on
Emotion Recognition in Conversation
on DailyDialog
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation
SenticNet/conv-emotion
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IJCNLP 2019
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
SenticNet/conv-emotion
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EMNLP 2018
Emotion recognition in conversations is crucial for building empathetic machines.
Ranked #5 on
Emotion Recognition in Conversation
on SEMAINE
Emotion Recognition in Conversation
General Classification
+1
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
SenticNet/conv-emotion
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NAACL 2018
Emotion recognition in conversations is crucial for the development of empathetic machines.
Ranked #7 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.
Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors
A2Zadeh/CMU-MultimodalDataSDK
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Humans convey their intentions through the usage of both verbal and nonverbal behaviors during face-to-face communication.
