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 151200 of 458 papers

TitleStatusHype
Emotion Classification of COVID-19 Chinese Microblogs based on the Emotion Category Description0
Emotion Corpus Construction Based on Selection from Hashtags0
Emotion Detection from EEG using Transfer Learning0
Emotion Detection through Body Gesture and Face0
Emotion Detection with Transformers: A Comparative Study0
Emotion Distribution Learning from Texts0
Automatic Emotion Experiencer Recognition0
Emotion Intensity and its Control for Emotional Voice Conversion0
Extending RNN-T-based speech recognition systems with emotion and language classification0
Emotion Analysis of Tweets Banning Education in Afghanistan0
Emotion recognition by fusing time synchronous and time asynchronous representations0
Emotion Recognition from Microblog Managing Emoticon with Text and Classifying using 1D CNN0
Anubhuti -- An annotated dataset for emotional analysis of Bengali short stories0
Emotion Recognition under Consideration of the Emotion Component Process Model0
Emotions and NLP: Future Directions0
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation0
EmotionX-AR: CNN-DCNN autoencoder based Emotion Classifier0
EmotionX-Area66: Predicting Emotions in Dialogues using Hierarchical Attention Network with Sequence Labeling0
EmotionX-DLC: Self-Attentive BiLSTM for Detecting Sequential Emotions in Dialogues0
EmotionX-DLC: Self-Attentive BiLSTM for Detecting Sequential Emotions in Dialogue0
EmotionX-HSU: Adopting Pre-trained BERT for Emotion Classification0
EmotionX-JTML: Detecting emotions with Attention0
EmoTweet-28: A Fine-Grained Emotion Corpus for Sentiment Analysis0
Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification0
EMOVIE: A Mandarin Emotion Speech Dataset with a Simple Emotional Text-to-Speech Model0
\#Emotional Tweets0
EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet0
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages0
Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models0
Causing Emotion in Collocation:An Exploratory Data Analysis0
EMTC: Multilabel Corpus in Movie Domain for Emotion Analysis in Conversational Text0
English-Malay Word Embeddings Alignment for Cross-lingual Emotion Classification with Hierarchical Attention Network0
English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts0
Converting Sentiment Annotated Data to Emotion Annotated Data0
Enhanced Multimodal Representation Learning with Cross-modal KD0
Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video0
Enhancing Emotion Prediction in News Headlines: Insights from ChatGPT and Seq2Seq Models for Free-Text Generation0
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning0
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features0
Ensemble emotion recognizing with multiple modal physiological signals0
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation0
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors0
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding0
Evaluating the Effectiveness of Data Augmentation for Emotion Classification in Low-Resource Settings0
Event Based Emotion Classification for News Articles0
Experiencer-Specific Emotion and Appraisal Prediction0
Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?0
Experimenting with Distant Supervision for Emotion Classification0
Exploiting Community Emotion for Microblog Event Detection0
CAiRE_HKUST at SemEval-2019 Task 3: Hierarchical Attention for Dialogue Emotion Classification0
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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