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

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Showing 251–275 of 458 papers

TitleStatusHype
General-Purpose Speech Representation Learning through a Self-Supervised Multi-Granularity Framework—0
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 Study—0
Exploring Deep Neural Networks and Transfer Learning for Analyzing Emotions in Tweets—0
Exploiting Narrative Context and A Priori Knowledge of Categories in Textual Emotion Classification—0
Emotion Classification by Jointly Learning to Lexiconize and Classify—0
Parsing Indian English News Headlines—0
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation—0
Investigating Emotion-Color Association in Deep Neural NetworksCode0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification—0
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions—0
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 Recognition—0
Speech-Based Emotion Recognition using Neural Networks and Information VisualizationCode0
Emotion recognition by fusing time synchronous and time asynchronous representations—0
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 Gestures—0
Investigating Emotion-Color Association in Deep Neural Networks—0
Anubhuti -- An annotated dataset for emotional analysis of Bengali short stories—0
Attention Driven Fusion for Multi-Modal Emotion Recognition—0
EmoGraph: Capturing Emotion Correlations using Graph Networks—0
How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter—0
Emotion Carrier Recognition from Personal Narratives—0
EigenEmo: Spectral Utterance Representation Using Dynamic Mode Decomposition for Speech Emotion Classification—0
Shallow over Deep Neural Networks: A empirical analysis for human emotion classification using audio data—0
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All datasetsCMU-MOSEISemEval 2018 Task 1E-cEWALKMFAROCStoriesArmanEmoCAER-DynamicRAVDESSShortPersianEmo

Benchmark Results

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