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 551–575 of 2041 papers

TitleStatusHype
ED-TTS: Multi-Scale Emotion Modeling using Cross-Domain Emotion Diarization for Emotional Speech Synthesis—0
Utilizing deep learning models for the identification of enhancers and super-enhancers based on genomic and epigenomic features—0
EVOKE: Emotion Enabled Virtual Avatar Mapping Using Optimized Knowledge Distillation—0
TemporalAugmenter: An Ensemble Recurrent Based Deep Learning Approach for Signal Classification—0
Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thought—0
TONE: A 3-Tiered ONtology for Emotion analysisCode0
HiCMAE: Hierarchical Contrastive Masked Autoencoder for Self-Supervised Audio-Visual Emotion RecognitionCode2
Bridging Modalities: Knowledge Distillation and Masked Training for Translating Multi-Modal Emotion Recognition to Uni-Modal, Speech-Only Emotion RecognitionCode0
Multi-Source Domain Adaptation with Transformer-based Feature Generation for Subject-Independent EEG-based Emotion Recognition—0
A Two-Stage Multimodal Emotion Recognition Model Based on Graph Contrastive Learning—0
IdentiFace : A VGG Based Multimodal Facial Biometric SystemCode1
MART: Masked Affective RepresenTation Learning via Masked Temporal Distribution Distillation—0
SVFAP: Self-supervised Video Facial Affect PerceiverCode1
A Multi-Task, Multi-Modal Approach for Predicting Categorical and Dimensional Emotions—0
Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition—0
Frame-level emotional state alignment method for speech emotion recognitionCode1
Modality-Collaborative Transformer with Hybrid Feature Reconstruction for Robust Emotion RecognitionCode0
DSNet: Disentangled Siamese Network with Neutral Calibration for Speech Emotion Recognition—0
emotion2vec: Self-Supervised Pre-Training for Speech Emotion RepresentationCode3
Leveraged Mel spectrograms using Harmonic and Percussive Components in Speech Emotion RecognitionCode0
An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition PerformanceCode0
Investigating salient representations and label Variance in Dimensional Speech Emotion Analysis—0
Facial Emotion Recognition using CNN in PyTorch—0
DER-GCN: Dialogue and Event Relation-Aware Graph Convolutional Neural Network for Multimodal Dialogue Emotion Recognition—0
CARAT: Contrastive Feature Reconstruction and Aggregation for Multi-Modal Multi-Label 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