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Emotion Classification

Emotion classification, or emotion categorization, is the task of recognising emotions to classify them into the corresponding category. Given an input, classify it as 'neutral or no emotion' or as one, or more, of several given emotions that best represent the mental state of the subject's facial expression, words, and so on. Some example benchmarks include ROCStories, Many Faces of Anger (MFA), and GoEmotions. Models can be evaluated using metrics such as the Concordance Correlation Coefficient (CCC) and the Mean Squared Error (MSE).

Papers

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Showing 426–450 of 458 papers

TitleStatusHype
The Many Faces of Anger: A Multicultural Video Dataset of Negative Emotions in the Wild (MFA-Wild)Code0
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian TextsCode0
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion RecognitionCode0
Real-time Convolutional Neural Networks for Emotion and Gender ClassificationCode0
Enhancing Cognitive Models of Emotions with Representation LearningCode0
Is Style All You Need? Dependencies Between Emotion and GST-based Speaker RecognitionCode0
Speech Emotion Recognition Using Multi-hop Attention MechanismCode0
Classifying and Visualizing Emotions with Emotional DANCode0
Multimodal Speech Emotion Recognition Using Audio and TextCode0
Uncovering the Limits of Text-based Emotion DetectionCode0
Towards Wide Learning: Experiments in HealthcareCode0
KAM -- a Kernel Attention Module for Emotion Classification with EEG DataCode0
What About Emotions? Guiding Fine-Grained Emotion Extraction from Mobile App ReviewsCode0
Multitask Learning for Emotionally Analyzing Sexual Abuse DisclosuresCode0
Emotion Action Detection and Emotion Inference: the Task and DatasetCode0
Transfer Learning for Improving Speech Emotion Classification AccuracyCode0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
Large Vision-Language Models for Knowledge-Grounded Data Annotation of MemesCode0
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational AgentsCode0
TinyEmo: Scaling down Emotional Reasoning via Metric ProjectionCode0
BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion ClassificationCode0
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-TrainingCode0
TONE: A 3-Tiered ONtology for Emotion analysisCode0
An Ensemble Approach to Detect Emotions at an Essay LevelCode0
Leaving Some Facial Features BehindCode0
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All datasetsCMU-MOSEISemEval 2018 Task 1E-cEWALKMFAROCStoriesArmanEmoCAER-DynamicRAVDESSShortPersianEmo

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MARLIN (ViT-L)Accuracy80.63—Unverified
2MARLIN (ViT-B)Accuracy80.6—Unverified
3MARLIN (ViT-S)Accuracy80.38—Unverified
4ConCluGenAccuracy66.48—Unverified
#ModelMetricClaimedVerifiedStatus
1SpanEmoAccuracy0.6—Unverified
2BERT+DKAccuracy0.59—Unverified
3BERT-GCNAccuracy0.59—Unverified
4Transformer (finetune)Macro-F10.56—Unverified
#ModelMetricClaimedVerifiedStatus
1ProxEmo (ours)Accuracy82.4—Unverified
2STEP [bhattacharya2019step]Accuracy78.24—Unverified
3Baseline (Vanilla LSTM) [Ewalk]Accuracy55.47—Unverified
#ModelMetricClaimedVerifiedStatus
1MLKNNF-F1 score (Comb.)0.34—Unverified
2CC - XGBF-F1 score (Comb.)0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1Semi-supervisionF165.88—Unverified
2NPN + Explanation TrainingF130.29—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.65—Unverified
#ModelMetricClaimedVerifiedStatus
1CAERNetAccuracy77.04—Unverified
#ModelMetricClaimedVerifiedStatus
1ERANN-0-4Top-1 Accuracy74.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.71—Unverified