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 351–400 of 458 papers

TitleStatusHype
Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content—0
Persian Slang Text Conversion to Formal and Deep Learning of Persian Short Texts on Social Media for Sentiment Classification—0
Unveiling Emotions from EEG: A GRU-Based Approach—0
PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and \#hashtags—0
Podlab at SemEval-2019 Task 3: The Importance of Being Shallow—0
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text—0
Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing—0
UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings—0
Probabilistic Ensembles of Zero- and Few-Shot Learning Models for Emotion Classification—0
AffecThor at SemEval-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets—0
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis—0
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations—0
A Comparison of Personalized and Generalized Approaches to Emotion Recognition Using Consumer Wearable Devices: Machine Learning Study—0
Real-time Emotion and Gender Classification using Ensemble CNN—0
Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework—0
Recent Advancement of Emotion Cognition in Large Language Models—0
RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification—0
Representation learning through cross-modal conditional teacher-student training for speech emotion recognition—0
Rethinking Multimodal Sentiment Analysis: A High-Accuracy, Simplified Fusion Architecture—0
Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion—0
Risk prediction of pathological gambling on social media—0
See Your Heart: Psychological states Interpretation through Visual Creations—0
Selective Co-occurrences for Word-Emotion Association—0
SemEval-2018 Task 1: Affect in Tweets—0
Semi-Automatic Construction and Refinement of an Annotated Corpus for a Deep Learning Framework for Emotion Classification—0
SensoryT5: Infusing Sensorimotor Norms into T5 for Enhanced Fine-grained Emotion Classification—0
Sentence and Clause Level Emotion Annotation, Detection, and Classification in a Multi-Genre Corpus—0
Sentence-level Emotion Classification with Label and Context Dependence—0
Sentence-Level Propaganda Detection in News Articles with Transfer Learning and BERT-BiLSTM-Capsule Model—0
Advanced LSTM: A Study about Better Time Dependency Modeling in Emotion Recognition—0
Sentiment Analysis in Twitter Social Network Centered on Cryptocurrencies Using Machine Learning—0
Sentiment and Emotion Classification of Epidemic Related Bilingual data from Social Media—0
SentiXRL: An advanced large language Model Framework for Multilingual Fine-Grained Emotion Classification in Complex Text Environment—0
Seq2Emo: A Sequence to Multi-Label Emotion Classification Model—0
Seq2Emo for Multi-label Emotion Classification Based on Latent Variable Chains Transformation—0
Shallow over Deep Neural Networks: A empirical analysis for human emotion classification using audio data—0
SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians—0
SINAI at IEST 2018: Neural Encoding of Emotional External Knowledge for Emotion Classification—0
SINAI at SemEval-2018 Task 1: Emotion Recognition in Tweets—0
SINAI at SemEval-2019 Task 3: Using affective features for emotion classification in textual conversations—0
Sociolinguistically Informed Interpretability: A Case Study on Hinglish Emotion Classification—0
A Simple Attention-Based Mechanism for Bimodal Emotion Classification—0
Aspect-Based Emotion Analysis and Multimodal Coreference: A Case Study of Customer Comments on Adidas Instagram Posts—0
A Study on Using Transfer Learning to Improve BERT Model for Emotional Classification of Chinese Lyrics—0
A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAG—0
A Topic Model for Building Fine-grained Domain-specific Emotion Lexicon—0
A transformer-based approach to video frame-level prediction in Affective Behaviour Analysis In-the-wild—0
Attention Driven Fusion for Multi-Modal Emotion Recognition—0
Attentive Cross-modal Connections for Deep Multimodal Wearable-based Emotion Recognition—0
Song Emotion Classification of Lyrics with Out-of-Domain Data under Label Scarcity—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