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 176–200 of 458 papers

TitleStatusHype
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations—0
EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition—0
x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations—0
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition—0
Towards Building an Open-Domain Dialogue System Incorporated with Internet Memes—0
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors—0
Deep Learning Neural Networks for Emotion Classification from Text: Enhanced Leaky Rectified Linear Unit Activation and Weighted Loss—0
Is Cross-Attention Preferable to Self-Attention for Multi-Modal Emotion Recognition?Code1
PARSE: Pairwise Alignment of Representations in Semi-Supervised EEG Learning for Emotion RecognitionCode1
Spectro Temporal EEG Biomarkers For Binary Emotion Classification—0
A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation—0
Automated Feature Extraction on AsMap for Emotion Classification using EEG—0
Domain-Invariant Representation Learning from EEG with Private EncodersCode1
Learning to Compose Diversified Prompts for Image Emotion Classification—0
A Pre-trained Audio-Visual Transformer for Emotion Recognition—0
Adaptive Transfer Learning for Multi-Label Emotion Classification—0
Emotion Intensity and its Control for Emotional Voice Conversion—0
Temporal Analysis of Functional Brain Connectivity for EEG-based Emotion Recognition—0
The Many Faces of Anger: A Multicultural Video Dataset of Negative Emotions in the Wild (MFA-Wild)Code0
Representation learning through cross-modal conditional teacher-student training for speech emotion recognition—0
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features—0
Knowledge-guided Transformer for Joint Theme and Emotion Classification of Chinese Classical Poetry—0
Real-time Emotion and Gender Classification using Ensemble CNN—0
Emotion Classification in German Plays with Transformer-based Language Models Pretrained on Historical and Contemporary LanguageCode0
MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition—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