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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 231–240 of 458 papers

Title	Date	Tasks	Status	Hype
Enhancing Cognitive Models of Emotions with Representation Learning	Apr 20, 2021	Emotion ClassificationRepresentation Learning	CodeCode Available	0
Emotion Classification in a Resource Constrained Language Using Transformer-based Approach	Apr 17, 2021	ClassificationEmotion Classification	CodeCode Available	1
AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification	Apr 9, 2021	ClassificationEmotion Classification	—Unverified	0
MilaNLP @ WASSA: Does BERT Feel Sad When You Cry?	Apr 1, 2021	Emotion ClassificationMulti-Task Learning	—Unverified	0
Multi-Emotion Classification for Song Lyrics	Apr 1, 2021	ClassificationEmotion Classification	—Unverified	0
Universal Joy A Data Set and Results for Classifying Emotions Across Languages	Apr 1, 2021	DiversityEmotion Classification	—Unverified	0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks	Mar 31, 2021	Emotion ClassificationFace Identification	—Unverified	0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks	Mar 31, 2021	Emotion ClassificationEmotion Recognition	—Unverified	0
Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework	Mar 29, 2021	Action Unit DetectionEmotion Classification	—Unverified	0
Real-Time Emotion Classification Using EEG Data Stream in E-Learning Contexts	Feb 25, 2021	ClassificationEEG	CodeCode Available	1

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All datasets CMU-MOSEI SemEval 2018 Task 1E-c EWALK MFA ROCStories ArmanEmo CAER-Dynamic RAVDESS ShortPersianEmo

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MARLIN (ViT-L)	Accuracy	80.63	—	Unverified
2	MARLIN (ViT-B)	Accuracy	80.6	—	Unverified
3	MARLIN (ViT-S)	Accuracy	80.38	—	Unverified
4	ConCluGen	Accuracy	66.48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SpanEmo	Accuracy	0.6	—	Unverified
2	BERT+DK	Accuracy	0.59	—	Unverified
3	BERT-GCN	Accuracy	0.59	—	Unverified
4	Transformer (finetune)	Macro-F1	0.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ProxEmo (ours)	Accuracy	82.4	—	Unverified
2	STEP [bhattacharya2019step]	Accuracy	78.24	—	Unverified
3	Baseline (Vanilla LSTM) [Ewalk]	Accuracy	55.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MLKNN	F-F1 score (Comb.)	0.34	—	Unverified
2	CC - XGB	F-F1 score (Comb.)	0.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Semi-supervision	F1	65.88	—	Unverified
2	NPN + Explanation Training	F1	30.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Deep ParsBERT	Macro F1	0.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CAERNet	Accuracy	77.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ERANN-0-4	Top-1 Accuracy	74.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Deep ParsBERT	Macro F1	0.71	—	Unverified