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 401425 of 458 papers

TitleStatusHype
Emotion Transfer Using Vector-Valued Infinite Task LearningCode0
PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion RegressionCode0
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language ModelsCode0
Emotion Recognition from SpeechCode0
Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised ModelsCode0
Minimax Filter: Learning to Preserve Privacy from Inference AttacksCode0
BYEL : Bootstrap Your Emotion LatentCode0
MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMsCode0
Emotion Classification in German Plays with Transformer-based Language Models Pretrained on Historical and Contemporary LanguageCode0
Transformer-based Text Classification on Unified Bangla Multi-class Emotion CorpusCode0
IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word RepresentationsCode0
PetKaz at SemEval-2024 Task 3: Advancing Emotion Classification with an LLM for Emotion-Cause Pair Extraction in ConversationsCode0
ArmanEmo: A Persian Dataset for Text-based Emotion DetectionCode0
Impact of time and note duration tokenizations on deep learning symbolic music modelingCode0
Improved acoustic-to-articulatory inversion using representations from pretrained self-supervised learning modelsCode0
A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG DataCode0
Cross-lingual Emotion Intensity PredictionCode0
Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss FunctionCode0
Pop Music Highlighter: Marking the Emotion KeypointsCode0
Practical Text Classification With Large Pre-Trained Language ModelsCode0
Inducing a Lexicon of Abusive Words – a Feature-Based ApproachCode0
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair AnalysisCode0
Context-Aware Emotion Recognition NetworksCode0
Towards More Accurate Prediction of Human Empathy and Emotion in Text and Multi-turn Conversations by Combining Advanced NLP, Transformers-based Networks, and Linguistic MethodologiesCode0
Investigating Emotion-Color Association in Deep Neural NetworksCode0
Show:102550
← PrevPage 17 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