SOTAVerified

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

Showing 376400 of 458 papers

TitleStatusHype
Objective Human Affective Vocal Expression Detection and Automatic Classification with Stochastic Models and Learning Systems0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models0
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition0
Parsing Indian English News Headlines0
Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content0
Persian Slang Text Conversion to Formal and Deep Learning of Persian Short Texts on Social Media for Sentiment Classification0
PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and \#hashtags0
Podlab at SemEval-2019 Task 3: The Importance of Being Shallow0
Probabilistic Ensembles of Zero- and Few-Shot Learning Models for Emotion Classification0
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis0
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel AttentionCode0
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution NetworksCode0
NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer LearningCode0
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNNCode0
NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion AnalysisCode0
Transformer based neural networks for emotion recognition in conversationsCode0
Attentive Modality Hopping Mechanism for Speech Emotion RecognitionCode0
Dimensional Emotion Detection from Categorical EmotionCode0
DataSEARCH at IEST 2018: Multiple Word Embedding based Models for Implicit Emotion Classification of Tweets with Deep LearningCode0
EmoTxt: A Toolkit for Emotion Recognition from TextCode0
Facial Affect Recognition in the Wild Using Multi-Task Learning Convolutional NetworkCode0
Extending Adversarial Attacks to Produce Adversarial Class Probability DistributionsCode0
Exploiting Multiple EEG Data Domains with Adversarial LearningCode0
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classificationCode0
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural AnnotatorsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MARLIN (ViT-L)Accuracy80.63Unverified
2MARLIN (ViT-B)Accuracy80.6Unverified
3MARLIN (ViT-S)Accuracy80.38Unverified
4ConCluGenAccuracy66.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpanEmoAccuracy0.6Unverified
2BERT+DKAccuracy0.59Unverified
3BERT-GCNAccuracy0.59Unverified
4Transformer (finetune)Macro-F10.56Unverified
#ModelMetricClaimedVerifiedStatus
1ProxEmo (ours)Accuracy82.4Unverified
2STEP [bhattacharya2019step]Accuracy78.24Unverified
3Baseline (Vanilla LSTM) [Ewalk]Accuracy55.47Unverified
#ModelMetricClaimedVerifiedStatus
1MLKNNF-F1 score (Comb.)0.34Unverified
2CC - XGBF-F1 score (Comb.)0.33Unverified
#ModelMetricClaimedVerifiedStatus
1Semi-supervisionF165.88Unverified
2NPN + Explanation TrainingF130.29Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.65Unverified
#ModelMetricClaimedVerifiedStatus
1CAERNetAccuracy77.04Unverified
#ModelMetricClaimedVerifiedStatus
1ERANN-0-4Top-1 Accuracy74.8Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.71Unverified