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 431–440 of 458 papers

Title	Date	Tasks	Status
Continuous Adversarial Text Representation Learning for Affective Recognition	Feb 28, 2025	Adversarial TextContrastive Learning	—Unverified
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages	Mar 28, 2022	DenoisingEmotion Classification	—Unverified
Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition	Sep 20, 2021	Contrastive LearningEEG	—Unverified
Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning	Aug 23, 2019	ClassificationEmotion Classification	—Unverified
Converting Sentiment Annotated Data to Emotion Annotated Data	Dec 1, 2019	Emotion ClassificationEmotion Recognition	—Unverified
Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video	Nov 13, 2017	Emotion ClassificationEmotion Recognition	—Unverified
Corpus Fusion for Emotion Classification	Dec 1, 2016	BIG-bench Machine LearningClassification	—Unverified
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features	Nov 16, 2021	Cultural Vocal Bursts Intensity PredictionEmotion Classification	—Unverified
Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers	Jun 23, 2023	Emotion ClassificationEmotion Recognition	—Unverified
ST-Gait++: Leveraging spatio-temporal convolutions for gait-based emotion recognition on videos	May 22, 2024	Emotion ClassificationEmotion Recognition	—Unverified

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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