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 101150 of 458 papers

TitleStatusHype
Facial Affect Recognition in the Wild Using Multi-Task Learning Convolutional NetworkCode0
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language ModelsCode0
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel AttentionCode0
DataSEARCH at IEST 2018: Multiple Word Embedding based Models for Implicit Emotion Classification of Tweets with Deep LearningCode0
IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word RepresentationsCode0
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural AnnotatorsCode0
Enhancing Cognitive Models of Emotions with Representation LearningCode0
Exploiting Multiple EEG Data Domains with Adversarial LearningCode0
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion RecognitionCode0
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational AgentsCode0
Emotion Recognition from SpeechCode0
Emotion Transfer Using Vector-Valued Infinite Task LearningCode0
Extending Adversarial Attacks to Produce Adversarial Class Probability DistributionsCode0
Impact of time and note duration tokenizations on deep learning symbolic music modelingCode0
MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMsCode0
Emotion4MIDI: a Lyrics-based Emotion-Labeled Symbolic Music DatasetCode0
BYEL : Bootstrap Your Emotion LatentCode0
EigenEmo: Spectral Utterance Representation Using Dynamic Mode Decomposition for Speech Emotion Classification0
ECSP: A New Task for Emotion-Cause Span-Pair Extraction and Classification0
Automatically Classifying Emotions based on Text: A Comparative Exploration of Different Datasets0
An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs0
ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models0
Automatically augmenting an emotion dataset improves classification using audio0
EEG emotion recognition using dynamical graph convolutional neural networks0
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions0
DMGroup at EmoInt-2017: Emotion Intensity Using Ensemble Method0
Automated Feature Extraction on AsMap for Emotion Classification using EEG0
An Emotional Comfort Framework for Improving User Satisfaction in E-Commerce Customer Service Chatbots0
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text0
DL Team at SemEval-2018 Task 1: Tweet Affect Detection using Sentiment Lexicons and Embeddings0
Distributed Representations of Emotion Categories in Emotion Space0
A Two-Stage Multimodal Emotion Recognition Model Based on Graph Contrastive Learning0
Disney at IEST 2018: Predicting Emotions using an Ensemble0
Discriminating Neutral and Emotional Speech using Neural Networks0
AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification0
An Analysis of Annotated Corpora for Emotion Classification in Text0
ZSDEVC: Zero-Shot Diffusion-based Emotional Voice Conversion with Disentangled Mechanism0
Attentive Cross-modal Connections for Deep Multimodal Wearable-based Emotion Recognition0
Analysing the Greek Parliament Records with Emotion Classification0
AffecThor at SemEval-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets0
A Comprehensive Analysis of Preprocessing for Word Representation Learning in Affective Tasks0
Detection and Analysis of Emotion From Speech Signals0
Deep Learning Neural Networks for Emotion Classification from Text: Enhanced Leaky Rectified Linear Unit Activation and Weighted Loss0
Attention Driven Fusion for Multi-Modal Emotion Recognition0
DeepEmotex: Classifying Emotion in Text Messages using Deep Transfer Learning0
A transformer-based approach to video frame-level prediction in Affective Behaviour Analysis In-the-wild0
An adversarial learning framework for preserving users' anonymity in face-based emotion recognition0
deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets0
Decoding Emotions in Abstract Art: Cognitive Plausibility of CLIP in Recognizing Color-Emotion Associations0
A Topic Model for Building Fine-grained Domain-specific Emotion Lexicon0
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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