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

Showing 151175 of 2041 papers

TitleStatusHype
EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTaCode1
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning SettingsCode1
EmoDynamiX: Emotional Support Dialogue Strategy Prediction by Modelling MiXed Emotions and Discourse DynamicsCode1
Emotion-Qwen: Training Hybrid Experts for Unified Emotion and General Vision-Language UnderstandingCode1
A Transformer-based joint-encoding for Emotion Recognition and Sentiment AnalysisCode1
Emotion Recognition on large video dataset based on Convolutional Feature Extractor and Recurrent Neural NetworkCode1
ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational AgentsCode1
EmoVIT: Revolutionizing Emotion Insights with Visual Instruction TuningCode1
A Efficient Multimodal Framework for Large Scale Emotion Recognition by Fusing Music and Electrodermal Activity SignalsCode1
ChatGPT: Jack of all trades, master of noneCode1
CLARA: Multilingual Contrastive Learning for Audio Representation AcquisitionCode1
Cluster-Level Contrastive Learning for Emotion Recognition in ConversationsCode1
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party ConversationsCode1
Codified audio language modeling learns useful representations for music information retrievalCode1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
Evaluation in EEG Emotion Recognition: State-of-the-Art Review and Unified FrameworkCode1
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in ConversationsCode1
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
Exploring Remote Physiological Signal Measurement under Dynamic Lighting Conditions at Night: Dataset, Experiment, and AnalysisCode1
Context Based Emotion Recognition using EMOTIC DatasetCode1
Facial Affective Behavior Analysis with Instruction TuningCode1
Facial Emotion Recognition Using Transfer Learning in the Deep CNNCode1
Facial Emotion Recognition with Noisy Multi-task AnnotationsCode1
A Supervised Information Enhanced Multi-Granularity Contrastive Learning Framework for EEG Based Emotion RecognitionCode1
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Benchmark Results

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