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 251275 of 458 papers

TitleStatusHype
Investigating Emotion-Color Association in Deep Neural NetworksCode0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification0
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions0
Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?0
Multiscale Fractal Analysis on EEG Signals for Music-Induced Emotion Recognition0
Speech-Based Emotion Recognition using Neural Networks and Information VisualizationCode0
Perception for Autonomous Systems (PAZ)Code1
Emotion recognition by fusing time synchronous and time asynchronous representations0
Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised ModelsCode0
A Generalized Zero-Shot Framework for Emotion Recognition from Body Gestures0
Investigating Emotion-Color Association in Deep Neural Networks0
Anubhuti -- An annotated dataset for emotional analysis of Bengali short stories0
Attention Driven Fusion for Multi-Modal Emotion Recognition0
EmoGraph: Capturing Emotion Correlations using Graph Networks0
How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter0
Emotion Carrier Recognition from Personal Narratives0
EigenEmo: Spectral Utterance Representation Using Dynamic Mode Decomposition for Speech Emotion Classification0
Shallow over Deep Neural Networks: A empirical analysis for human emotion classification using audio data0
Contextualized Emotion Recognition in Conversation as Sequence Tagging0
More Diverse Dialogue Datasets via Diversity-Informed Data Collection0
A Comprehensive Analysis of Preprocessing for Word Representation Learning in Affective Tasks0
Modeling Label Semantics for Predicting Emotional ReactionsCode1
Team Neuro at SemEval-2020 Task 8: Multi-Modal Fine Grain Emotion Classification of Memes using Multitask Learning0
A computational model implementing subjectivity with the 'Room Theory'. The case of detecting Emotion from Text0
SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment SemanticsCode1
Show:102550
← PrevPage 11 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