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

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Showing 51–100 of 458 papers

TitleStatusHype
Interpretable Multi-Task PINN for Emotion Recognition and EDA Prediction—0
EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese MetaphorsCode0
Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture—0
Emo Pillars: Knowledge Distillation to Support Fine-Grained Context-Aware and Context-Less Emotion Classification—0
SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians—0
Integrating Emotion Distribution Networks and Textual Message Analysis for X User Emotional State Classification—0
A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAG—0
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations—0
Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation—0
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text—0
Machine learning based animal emotion classification using audio signals—0
Symbolic Audio Classification via Modal Decision Tree Learning—0
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations—0
Continuous Adversarial Text Representation Learning for Affective Recognition—0
Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion ClassificationCode0
A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions—0
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition—0
Characteristic-Specific Partial Fine-Tuning for Efficient Emotion and Speaker Adaptation in Codec Language Text-to-Speech Models—0
Large Vision-Language Models for Knowledge-Grounded Data Annotation of MemesCode0
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition—0
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair AnalysisCode0
Sentiment Analysis in Twitter Social Network Centered on Cryptocurrencies Using Machine Learning—0
Deep Learning-Based Feature Fusion for Emotion Analysis and Suicide Risk Differentiation in Chinese Psychological Support HotlinesCode0
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding—0
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition—0
SentiXRL: An advanced large language Model Framework for Multilingual Fine-Grained Emotion Classification in Complex Text Environment—0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
Emotion Classification of Children Expressions—0
Exploring Vision Language Models for Facial Attribute Recognition: Emotion, Race, Gender, and Age—0
Multi-aspect Depression Severity Assessment via Inductive Dialogue System—0
Leaving Some Facial Features BehindCode0
VEMOCLAP: A video emotion classification web application—0
M2M-Gen: A Multimodal Framework for Automated Background Music Generation in Japanese Manga Using Large Language Models—0
TinyEmo: Scaling down Emotional Reasoning via Metric ProjectionCode0
Song Emotion Classification of Lyrics with Out-of-Domain Data under Label Scarcity—0
A Multi-task Learning Framework for Evaluating Machine Translation of Emotion-loaded User-generated Content—0
Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss FunctionCode0
Recent Advancement of Emotion Cognition in Large Language Models—0
ZSDEVC: Zero-Shot Diffusion-based Emotional Voice Conversion with Disentangled Mechanism—0
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
All rivers run into the sea: Unified Modality Brain-like Emotional Central Mechanism—0
An Explainable Fast Deep Neural Network for Emotion Recognition—0
Enhancing Emotion Prediction in News Headlines: Insights from ChatGPT and Seq2Seq Models for Free-Text Generation—0
Emotion Detection through Body Gesture and Face—0
Flood of Techniques and Drought of Theories: Emotion Mining in Disasters—0
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational AgentsCode0
A Simple Attention-Based Mechanism for Bimodal Emotion Classification—0
Evaluating the Effectiveness of Data Augmentation for Emotion Classification in Low-Resource Settings—0
Multi-Microphone Speech Emotion Recognition using the Hierarchical Token-semantic Audio Transformer Architecture—0
Annotation Guidelines-Based Knowledge Augmentation: Towards Enhancing Large Language Models for Educational Text Classification—0
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All datasetsCMU-MOSEISemEval 2018 Task 1E-cEWALKMFAROCStoriesArmanEmoCAER-DynamicRAVDESSShortPersianEmo

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MARLIN (ViT-L)Accuracy80.63—Unverified
2MARLIN (ViT-B)Accuracy80.6—Unverified
3MARLIN (ViT-S)Accuracy80.38—Unverified
4ConCluGenAccuracy66.48—Unverified
#ModelMetricClaimedVerifiedStatus
1SpanEmoAccuracy0.6—Unverified
2BERT+DKAccuracy0.59—Unverified
3BERT-GCNAccuracy0.59—Unverified
4Transformer (finetune)Macro-F10.56—Unverified
#ModelMetricClaimedVerifiedStatus
1ProxEmo (ours)Accuracy82.4—Unverified
2STEP [bhattacharya2019step]Accuracy78.24—Unverified
3Baseline (Vanilla LSTM) [Ewalk]Accuracy55.47—Unverified
#ModelMetricClaimedVerifiedStatus
1MLKNNF-F1 score (Comb.)0.34—Unverified
2CC - XGBF-F1 score (Comb.)0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1Semi-supervisionF165.88—Unverified
2NPN + Explanation TrainingF130.29—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.65—Unverified
#ModelMetricClaimedVerifiedStatus
1CAERNetAccuracy77.04—Unverified
#ModelMetricClaimedVerifiedStatus
1ERANN-0-4Top-1 Accuracy74.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.71—Unverified