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 201–210 of 458 papers

Title	Date	Tasks	Status
Exploiting Narrative Context and A Priori Knowledge of Categories in Textual Emotion Classification	Dec 1, 2020	Emotion ClassificationMulti-Task Learning	—Unverified
Exploratory Analysis of Social Media Prior to a Suicide Attempt	Jun 1, 2016	Emotion Classification	—Unverified
AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification	Apr 9, 2021	ClassificationEmotion Classification	—Unverified
Exploring Fine-Grained Emotion Detection in Tweets	Jun 1, 2016	Emotion ClassificationGeneral Classification	—Unverified
EmoTweet-28: A Fine-Grained Emotion Corpus for Sentiment Analysis	May 1, 2016	Emotion ClassificationGeneral Classification	—Unverified
Exploring Vision Language Models for Facial Attribute Recognition: Emotion, Race, Gender, and Age	Oct 31, 2024	AttributeEmotion Classification	—Unverified
Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification	May 1, 2022	AttributeClassification	—Unverified
Extending RNN-T-based speech recognition systems with emotion and language classification	Jul 28, 2022	Emotion ClassificationEmotion Recognition	—Unverified
EmotionX-JTML: Detecting emotions with Attention	Jul 1, 2018	Emotion ClassificationRepresentation Learning	—Unverified
EmotionX-HSU: Adopting Pre-trained BERT for Emotion Classification	Jul 23, 2019	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