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 1076–1100 of 2041 papers

TitleStatusHype
Multitask Emotion Recognition Model with Knowledge Distillation and Task Discriminator—0
Chat-Capsule: A Hierarchical Capsule for Dialog-level Emotion Analysis—0
x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations—0
EEG based Emotion Recognition: A Tutorial and Review—0
Emotion Recognition using Machine Learning and ECG signals—0
Semi-FedSER: Semi-supervised Learning for Speech Emotion Recognition On Federated Learning using Multiview Pseudo-LabelingCode1
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition—0
Audiovisual Affect Assessment and Autonomous Automobiles: Applications—0
Dawn of the transformer era in speech emotion recognition: closing the valence gapCode2
EventFormer: AU Event Transformer for Facial Action Unit Event Detection—0
Robust Federated Learning Against Adversarial Attacks for Speech Emotion Recognition—0
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors—0
Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributesCode0
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in ConversationsCode1
Attention-based Region of Interest (ROI) Detection for Speech Emotion Recognition—0
TRILLsson: Distilled Universal Paralinguistic Speech Representations—0
Towards a Common Speech Analysis Engine—0
DAGAM: A Domain Adversarial Graph Attention Model for Subject Independent EEG-Based Emotion Recognition—0
Novel techniques for improving NNetEn entropy calculation for short and noisy time series—0
Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG SignalsCode1
Enhancing Affective Representations of Music-Induced EEG through Multimodal Supervision and latent Domain AdaptationCode0
Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responsesCode1
Is Cross-Attention Preferable to Self-Attention for Multi-Modal Emotion Recognition?Code1
Multimodal Emotion Recognition using Transfer Learning from Speaker Recognition and BERT-based models—0
PARSE: Pairwise Alignment of Representations in Semi-Supervised EEG Learning for Emotion RecognitionCode1
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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