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 176–200 of 2041 papers

TitleStatusHype
Is It Still Fair? Investigating Gender Fairness in Cross-Corpus Speech Emotion Recognition—0
EMOE: Modality-Specific Enhanced Dynamic Emotion Experts—0
Unsupervised Discovery of Facial Landmarks and Head Pose—0
CocoER: Aligning Multi-Level Feature by Competition and Coordination for Emotion Recognition—0
A novel deep learning approach for facial emotion recognition: application to detecting emotional responses in elderly individuals with Alzheimer’s diseaseCode1
Metadata-Enhanced Speech Emotion Recognition: Augmented Residual Integration and Co-Attention in Two-Stage Fine-Tuning—0
Enhancing Multimodal Emotion Recognition through Multi-Granularity Cross-Modal Alignment—0
Sample Correlation for Fingerprinting Deep Face RecognitionCode0
Mouth Articulation-Based Anchoring for Improved Cross-Corpus Speech Emotion Recognition—0
Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-LearningCode1
A Multimodal Emotion Recognition System: Integrating Facial Expressions, Body Movement, Speech, and Spoken Language—0
Effective Context Modeling Framework for Emotion Recognition in Conversations—0
Prototypical Calibrating Ambiguous Samples for Micro-Action RecognitionCode1
Bridge then Begin Anew: Generating Target-relevant Intermediate Model for Source-free Visual Emotion AdaptationCode0
Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion RecognitionCode0
Enhanced Speech Emotion Recognition with Efficient Channel Attention Guided Deep CNN-BiLSTM Framework—0
Multimodal Sentiment Analysis based on Video and Audio Inputs—0
EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion UnderstandingCode1
My Words Imply Your Opinion: Reader Agent-Based Propagation Enhancement for Personalized Implicit Emotion Analysis—0
Depression detection from Social Media Bangla Text Using Recurrent Neural Networks—0
WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognition—0
Dynamic Graph Neural ODE Network for Multi-modal Emotion Recognition in Conversation—0
VR Based Emotion Recognition Using Deep Multimodal Fusion With Biosignals Across Multiple Anatomical Domains—0
Swin Transformer with Enhanced Dropout and Layer-wise Unfreezing for Facial Expression Recognition in Mental Health DetectionCode1
Cross-Task Inconsistency Based Active Learning (CTIAL) for 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