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 101125 of 458 papers

TitleStatusHype
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning0
ST-Gait++: Leveraging spatio-temporal convolutions for gait-based emotion recognition on videos0
Transformer based neural networks for emotion recognition in conversationsCode0
Decoding Emotions in Abstract Art: Cognitive Plausibility of CLIP in Recognizing Color-Emotion Associations0
Machine Learning-based NLP for Emotion Classification on a Cholera X Dataset0
Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion0
Two in One Go: Single-stage Emotion Recognition with Decoupled Subject-context Transformer0
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation0
Cepstral Analysis Based Artifact Detection, Recognition and Removal for Prefrontal EEG0
The Power of Properties: Uncovering the Influential Factors in Emotion Classification0
PetKaz at SemEval-2024 Task 3: Advancing Emotion Classification with an LLM for Emotion-Cause Pair Extraction in ConversationsCode0
Towards Bi-Hemispheric Emotion Mapping through EEG: A Dual-Stream Neural Network Approach0
Music Recommendation Based on Facial Emotion Recognition0
Improved Text Emotion Prediction Using Combined Valence and Arousal Ordinal Classification0
Risk prediction of pathological gambling on social media0
SensoryT5: Infusing Sensorimotor Norms into T5 for Enhanced Fine-grained Emotion Classification0
Emotion Detection with Transformers: A Comparative Study0
An Adaptive Cost-Sensitive Learning and Recursive Denoising Framework for Imbalanced SVM Classification0
Persian Slang Text Conversion to Formal and Deep Learning of Persian Short Texts on Social Media for Sentiment Classification0
Emotion Classification in Low and Moderate Resource Languages0
Emotion Classification in Short English Texts using Deep Learning Techniques0
Handling Ambiguity in Emotion: From Out-of-Domain Detection to Distribution Estimation0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models0
Sociolinguistically Informed Interpretability: A Case Study on Hinglish Emotion Classification0
English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts0
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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