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 2001–2041 of 2041 papers

TitleStatusHype
Deep Learning-Based Feature Fusion for Emotion Analysis and Suicide Risk Differentiation in Chinese Psychological Support HotlinesCode0
A speech corpus of Quechua Collao for automatic dimensional emotion recognitionCode0
Building a Large Scale Dataset for Image Emotion Recognition: The Fine Print and The BenchmarkCode0
PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion RegressionCode0
Enhancing Affective Representations of Music-Induced EEG through Multimodal Supervision and latent Domain AdaptationCode0
MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion RecognitionCode0
Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and ParaphrasingCode0
VAEmo: Efficient Representation Learning for Visual-Audio Emotion with Knowledge InjectionCode0
PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their RelationshipCode0
Persian Emotion Detection using ParsBERT and Imbalanced Data Handling ApproachesCode0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
End-to-End Multimodal Emotion Recognition using Deep Neural NetworksCode0
Unsupervised Cross-Lingual Speech Emotion Recognition Using Pseudo MultilabelCode0
The Many Faces of Anger: A Multicultural Video Dataset of Negative Emotions in the Wild (MFA-Wild)Code0
Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion MiningCode0
End-to-End Label Uncertainty Modeling in Speech Emotion Recognition using Bayesian Neural Networks and Label Distribution LearningCode0
ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving VehicleCode0
End-To-End Label Uncertainty Modeling for Speech-based Arousal Recognition Using Bayesian Neural NetworksCode0
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsCode0
MMCert: Provable Defense against Adversarial Attacks to Multi-modal ModelsCode0
ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion ModelingCode0
Analysis of Self-Supervised Learning and Dimensionality Reduction Methods in Clustering-Based Active Learning for Speech Emotion RecognitionCode0
EmoTxt: A Toolkit for Emotion Recognition from TextCode0
EmotionX-KU: BERT-Max based Contextual Emotion ClassifierCode0
EmotionX-IDEA: Emotion BERT -- an Affectional Model for ConversationCode0
Deep Learning based Emotion Recognition System Using Speech Features and TranscriptionsCode0
Building a Dialogue Corpus Annotated with Expressed and Experienced EmotionsCode0
Modality-Collaborative Transformer with Hybrid Feature Reconstruction for Robust Emotion RecognitionCode0
Deep Emotion Recognition in Textual Conversations: A SurveyCode0
Emotion Recognition Using Transformers with Masked LearningCode0
Modeling emotion in complex stories: the Stanford Emotional Narratives DatasetCode0
A Multi-task Neural Approach for Emotion Attribution, Classification and SummarizationCode0
DeepEmo: Learning and Enriching Pattern-Based Emotion RepresentationsCode0
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing FlowsCode0
PFML: Self-Supervised Learning of Time-Series Data Without Representation CollapseCode0
DeepEMO: Deep Learning for Speech Emotion RecognitionCode0
A Speech Representation Anonymization Framework via Selective Noise PerturbationCode0
Physically Disentangled RepresentationsCode0
Emotion Recognition of the Singing Voice: Toward a Real-Time Analysis Tool for SingersCode0
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and BeyondCode0
MONOVAB : An Annotated Corpus for Bangla Multi-label Emotion DetectionCode0
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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