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 301–310 of 458 papers

Title	Date	Tasks	Status
HGSGNLP at IEST 2018: An Ensemble of Machine Learning and Deep Neural Architectures for Implicit Emotion Classification in Tweets	Oct 1, 2018	Common Sense ReasoningEmotion Classification	—Unverified
Hierarchical Audio-Visual Information Fusion with Multi-label Joint Decoding for MER 2023	Sep 11, 2023	Emotion ClassificationEmotion Recognition	—Unverified
How Do I Look? Publicity Mining From Distributed Keyword Representation of Socially Infused News Articles	Nov 1, 2016	ArticlesEmotion Classification	—Unverified
How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter	Aug 20, 2020	Emotion Classification	—Unverified
Human Emotion Classification based on EEG Signals Using Recurrent Neural Network And KNN	May 10, 2022	Brain Computer Interfacechannel selection	—Unverified
Hybrid Facial Expression Recognition (FER2013) Model for Real-Time Emotion Classification and Prediction	Jun 19, 2022	Data AugmentationEmotion Classification	—Unverified
Hyperparameters optimization for Deep Learning based emotion prediction for Human Robot Interaction	Jan 12, 2020	Emotion ClassificationEmotion Recognition	—Unverified
IITP at IJCNLP-2017 Task 4: Auto Analysis of Customer Feedback using CNN and GRU Network	Dec 1, 2017	Document ClassificationEmotion Classification	—Unverified
I Know How You Feel: Emotion Recognition with Facial Landmarks	Apr 22, 2018	ClassificationEmotion Classification	—Unverified
Improved Speech Emotion Recognition using Transfer Learning and Spectrogram Augmentation	Aug 5, 2021	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