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 576–600 of 2041 papers

TitleStatusHype
Facial Emotion Recognition in VR Games—0
NAC-TCN: Temporal Convolutional Networks with Causal Dilated Neighborhood Attention for Emotion UnderstandingCode0
Testing Correctness, Fairness, and Robustness of Speech Emotion Recognition Models—0
Deep Imbalanced Learning for Multimodal Emotion Recognition in Conversations—0
Speech and Text-Based Emotion Recognizer—0
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing FlowsCode0
A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learning—0
GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion RecognitionCode1
Multimodal Group Emotion Recognition In-the-wild Using Privacy-Compliant Features—0
Understanding Environmental Posts: Sentiment and Emotion Analysis of Social Media Data—0
LineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks—0
ESTformer: Transformer Utilizing Spatiotemporal Dependencies for Electroencaphalogram Super-resolution—0
Facial Emotion Recognition Under Mask Coverage Using a Data Augmentation TechniqueCode0
Churn Prediction via Multimodal Fusion Learning:Integrating Customer Financial Literacy, Voice, and Behavioral Data—0
Optimal EEG Electrode Set for Emotion Recognition From Brain Signals: An Empirical Quest—0
SER_AMPEL: a multi-source dataset for speech emotion recognition of Italian older adults—0
Dialogue Quality and Emotion Annotations for Customer Support ConversationsCode0
End-to-end transfer learning for speaker-independent cross-language and cross-corpus speech emotion recognition—0
Leveraging Previous Facial Action Units Knowledge for Emotion Recognition on Faces—0
Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification TasksCode0
Implementation of AI Deep Learning Algorithm For Multi-Modal Sentiment Analysis—0
Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion RecognitionCode1
Utilizing Speech Emotion Recognition and Recommender Systems for Negative Emotion Handling in Therapy Chatbots—0
Enhancing Student Engagement in Online Learning through Facial Expression Analysis and Complex Emotion Recognition using Deep Learning—0
Improving Unimodal Inference with Multimodal Transformers—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