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 131–140 of 458 papers

Title	Date	Tasks	Status
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification	Nov 20, 2020	Emotion ClassificationGeneral Classification	—Unverified
Combining Contrastive and Non-Contrastive Losses for Fine-Tuning Pretrained Models in Speech Analysis	Oct 21, 2022	Emotion Classification	—Unverified
A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions	Feb 13, 2025	Emotion ClassificationEmotion Recognition	—Unverified
CNN based music emotion classification	Apr 19, 2017	ClassificationEmotion Classification	—Unverified
Cluster-based Deep Ensemble Learning for Emotion Classification in Internet Memes	Feb 16, 2023	ClusteringEmotion Classification	—Unverified
A Novel Approach for Effective Learning in Low Resourced Scenarios	Dec 15, 2017	BIG-bench Machine LearningClassification	—Unverified
A hierarchical approach with feature selection for emotion recognition from speech	May 1, 2012	ClassificationDimensionality Reduction	—Unverified
Annotation Guidelines-Based Knowledge Augmentation: Towards Enhancing Large Language Models for Educational Text Classification	Jun 3, 2024	Binary ClassificationClassification	—Unverified
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure	Aug 31, 2022	channel selectionClassification	—Unverified
AHD ConvNet for Speech Emotion Classification	Jun 10, 2022	ClassificationEmotion Classification	—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