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 151175 of 458 papers

TitleStatusHype
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion RecognitionCode1
SwahBERT: Language Model of Swahili0
YNU-HPCC at SemEval-2022 Task 5: Multi-Modal and Multi-label Emotion Classification Based on LXMERT0
Low Resource Pipeline for Spoken Language Understanding via Weak Supervision0
Hybrid Facial Expression Recognition (FER2013) Model for Real-Time Emotion Classification and Prediction0
Accurate Emotion Strength Assessment for Seen and Unseen Speech Based on Data-Driven Deep LearningCode1
DeepEmotex: Classifying Emotion in Text Messages using Deep Transfer Learning0
AHD ConvNet for Speech Emotion Classification0
RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification0
Aspect-Based Emotion Analysis and Multimodal Coreference: A Case Study of Customer Comments on Adidas Instagram Posts0
Nkululeko: A Tool For Rapid Speaker Characteristics DetectionCode1
Analysing the Greek Parliament Records with Emotion Classification0
Human Emotion Classification based on EEG Signals Using Recurrent Neural Network And KNN0
English-Malay Word Embeddings Alignment for Cross-lingual Emotion Classification with Hierarchical Attention Network0
IUCL at WASSA 2022 Shared Task: A Text-only Approach to Empathy and Emotion Detection0
Team IITP-AINLPML at WASSA 2022: Empathy Detection, Emotion Classification and Personality Detection0
Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification0
Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models0
Transformer-based Architecture for Empathy Prediction and Emotion Classification0
An Ensemble Approach to Detect Emotions at an Essay LevelCode0
None Class Ranking Loss for Document-Level Relation ExtractionCode1
Gaze-enhanced Crossmodal Embeddings for Emotion Recognition0
Leveraging Emotion-specific Features to Improve Transformer Performance for Emotion Classification0
Exploiting Multiple EEG Data Domains with Adversarial LearningCode0
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations0
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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