SOTAVerified

Emotion Recognition

Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition

Papers

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Showing 901–950 of 2041 papers

TitleStatusHype
Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition—0
Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion MiningCode0
"We care": Improving Code Mixed Speech Emotion Recognition in Customer-Care Conversations—0
Capturing Spectral and Long-term Contextual Information for Speech Emotion Recognition Using Deep Learning Techniques—0
Contextual Emotion Recognition Using Transformer-Based ModelsCode0
Using Scene and Semantic Features for Multi-modal Emotion Recognition—0
Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion—0
Self-Supervised Learning for Audio-Based Emotion Recognition—0
FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion RecognitionCode0
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality ConversionCode0
Cross-Corpus Multilingual Speech Emotion Recognition: Amharic vs. Other Languages—0
MASR: Multi-label Aware Speech Representation—0
Unveiling Emotions from EEG: A GRU-Based Approach—0
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection—0
Emotional Intelligence of Large Language Models—0
EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributes—0
Emotion recognition based on multi-modal electrophysiology multi-head attention Contrastive Learning—0
Emotion Analysis on EEG Signal Using Machine Learning and Neural Network—0
Evaluating raw waveforms with deep learning frameworks for speech emotion recognition—0
A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition—0
SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images—0
Human Emotion Recognition Based On Galvanic Skin Response signal Feature Selection and SVM—0
A Dual-Stream Recurrence-Attention Network With Global-Local Awareness for Emotion Recognition in Textual Dialog—0
Empirical Interpretation of the Relationship Between Speech Acoustic Context and Emotion Recognition—0
Emotion Analysis of Tweets Banning Education in Afghanistan—0
Exploiting Pseudo Future Contexts for Emotion Recognition in ConversationsCode0
Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers—0
TACOformer:Token-channel compounded Cross Attention for Multimodal Emotion Recognition—0
A Comparison of Time-based Models for Multimodal Emotion Recognition—0
A Low-rank Matching Attention based Cross-modal Feature Fusion Method for Conversational Emotion Recognition—0
FedMultimodal: A Benchmark For Multimodal Federated LearningCode0
SAFER: Situation Aware Facial Emotion Recognition—0
Continuous Learning Based Novelty Aware Emotion Recognition System—0
EMERSK -- Explainable Multimodal Emotion Recognition with Situational Knowledge—0
GEmo-CLAP: Gender-Attribute-Enhanced Contrastive Language-Audio Pretraining for Accurate Speech Emotion Recognition—0
Exploring Attention Mechanisms for Multimodal Emotion Recognition in an Emergency Call Center Corpus—0
MFSN: Multi-perspective Fusion Search Network For Pre-training Knowledge in Speech Emotion Recognition—0
Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and ParaphrasingCode0
Modality Influence in Multimodal Machine Learning—0
Learning Emotional Representations from Imbalanced Speech Data for Speech Emotion Recognition and Emotional Text-to-Speech—0
A Quantum Probability Driven Framework for Joint Multi-Modal Sarcasm, Sentiment and Emotion Analysis—0
Interpretable Multimodal Emotion Recognition using Facial Features and Physiological Signals—0
Synthesizing Affective Neurophysiological Signals Using Generative Models: A Review Paper—0
LDEB -- Label Digitization with Emotion Binarization and Machine Learning for Emotion Recognition in Conversational Dialogues—0
Leveraging Semantic Information for Efficient Self-Supervised Emotion Recognition with Audio-Textual Distilled Models—0
Transforming the Embeddings: A Lightweight Technique for Speech Emotion Recognition Tasks—0
ArPanEmo: An Open-Source Dataset for Fine-Grained Emotion Recognition in Arabic Online Content during COVID-19 Pandemic—0
Inter Subject Emotion Recognition Using Spatio-Temporal Features From EEG Signal—0
Automatic Emotion Experiencer Recognition—0
Transfer Learning for Personality Perception via Speech Emotion Recognition—0
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All datasetsEmomusicRAVDESSEMOTICFER2013MaSaC_ERCMPEDMSP-PodcastSEEDคลิปคุณพ่อให้ลูกสาวยืมโทรศัพท์และความสนุกสนาน

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1M2D-CLAPEmoA77.4—Unverified
2M2D2EmoA76.7—Unverified
3M2DEmoA76.1—Unverified
4Jukebox (Pre-training: CALM)EmoA72.1—Unverified
5CLMR (Pre-training: contrastive)EmoA67.8—Unverified
#ModelMetricClaimedVerifiedStatus
1LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+AttentionAccuracy86.7—Unverified
2MultiMAE-DERWAR83.61—Unverified
3Intermediate-Attention-FusionAccuracy81.58—Unverified
4Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedSTAccuracy80.08—Unverified
5ERANN-0-4Accuracy74.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CAGETop-3 Accuracy (%)14.73—Unverified
2FocusCLIPTop-3 Accuracy (%)13.73—Unverified
#ModelMetricClaimedVerifiedStatus
1VGG based5-class test accuracy66.13—Unverified
#ModelMetricClaimedVerifiedStatus
1MaSaC-ERC-ZF1-score (Weighted)51.17—Unverified
#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy40.34—Unverified
#ModelMetricClaimedVerifiedStatus
1w2v2-L-robust-12Concordance correlation coefficient (CCC)0.64—Unverified
#ModelMetricClaimedVerifiedStatus
14D-aNNAccuracy96.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN1'"1—Unverified