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 226250 of 458 papers

TitleStatusHype
Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task ApproachCode1
Magnifying Subtle Facial Motions for Effective 4D Expression Recognition0
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora0
Sentiment and Emotion Classification of Epidemic Related Bilingual data from Social Media0
WASSA@IITK at WASSA 2021: Multi-task Learning and Transformer Finetuning for Emotion Classification and Empathy Prediction0
Enhancing Cognitive Models of Emotions with Representation LearningCode0
Emotion Classification in a Resource Constrained Language Using Transformer-based ApproachCode1
AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification0
MilaNLP @ WASSA: Does BERT Feel Sad When You Cry?0
Multi-Emotion Classification for Song Lyrics0
Universal Joy A Data Set and Results for Classifying Emotions Across Languages0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks0
Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework0
Real-Time Emotion Classification Using EEG Data Stream in E-Learning ContextsCode1
Emotion Transfer Using Vector-Valued Infinite Task LearningCode0
General-Purpose Speech Representation Learning through a Self-Supervised Multi-Granularity Framework0
SpanEmo: Casting Multi-label Emotion Classification as Span-predictionCode1
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classificationCode0
Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study0
Exploring Deep Neural Networks and Transfer Learning for Analyzing Emotions in Tweets0
Parsing Indian English News Headlines0
Exploiting Narrative Context and A Priori Knowledge of Categories in Textual Emotion Classification0
Emotion Classification by Jointly Learning to Lexiconize and Classify0
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation0
Show:102550
← PrevPage 10 of 19Next →

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