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 16011650 of 2041 papers

TitleStatusHype
Adaptive Fusion Techniques for Multimodal Data0
M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues0
Addressing Ambiguity of Emotion Labels Through Meta-Learning0
Speaker-invariant Affective Representation Learning via Adversarial Training0
An Affective Situation Labeling System from Psychological Behaviors in Emotion Recognition0
Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis0
Modeling Feature Representations for Affective Speech using Generative Adversarial Networks0
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition0
DENS: A Dataset for Multi-class Emotion Analysis0
AI in Pursuit of Happiness, Finding Only Sadness: Multi-Modal Facial Emotion Recognition Challenge0
Domain adversarial learning for emotion recognition0
Unsupervised Representation Learning with Future Observation Prediction for Speech Emotion Recognition0
Multi-label Co-regularization for Semi-supervised Facial Action Unit RecognitionCode0
Conversational Emotion Analysis via Attention Mechanisms0
Emotion recognition with 4kresolution database0
Expression Analysis Based on Face Regions in Read-world Conditions0
Speech Emotion Recognition via Contrastive Loss under Siamese Networks0
Spatiotemporal Emotion Recognition using Deep CNN Based on EEG during Music ListeningCode0
Speech Emotion Recognition with Dual-Sequence LSTM Architecture0
PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion RecognitionCode1
Facial Emotion Recognition Using Deep Learning0
Indian EmoSpeech Command Dataset: A dataset for emotion based speech recognition in the wildCode0
Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network0
Self-supervised Learning for ECG-based Emotion RecognitionCode1
Interpretable Deep Neural Networks for Facial Expression and Dimensional Emotion Recognition in-the-wild0
Interpretable Deep Neural Networks for Dimensional and Categorical Emotion Recognition in-the-wild0
Emotion Generation and Recognition: A StarGAN Approach0
Facial Emotion Recognition using Convolutional Neural Networks0
Conversational Transfer Learning for Emotion Recognition0
A Deep Learning Based Chatbot for Campus Psychological Therapy0
BHAAV- A Text Corpus for Emotion Analysis from Hindi StoriesCode1
Linking emotions to behaviors through deep transfer learningCode0
Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset0
Automatic Group Cohesiveness Detection With Multi-modal Features0
Emotion Recognition with Spatial Attention and Temporal Softmax Pooling0
Zero-Shot Emotion Recognition via Affective Structural Embedding0
Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace0
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data BiasCode0
Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use CasesCode0
Student Engagement Detection Using Emotion Analysis, Eye Tracking and Head Movement with Machine LearningCode0
The emotions that we perceive in music: the influence of language and lyrics comprehension on agreement0
EEG based Emotion Recognition of Image Stimuli0
PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion RegressionCode0
HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for ElectroencephalographyCode0
Multimodal Embeddings from Language ModelsCode0
Learning Alignment for Multimodal Emotion Recognition from SpeechCode0
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning0
Sentiment and Emotion Based Representations for Fake Reviews Detection0
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
Emotion Recognition in Low-Resource Settings: An Evaluation of Automatic Feature Selection Methods0
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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