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 301–325 of 2041 papers

TitleStatusHype
Multitask Emotion Recognition with Incomplete LabelsCode1
Self-supervised ECG Representation Learning for Emotion RecognitionCode1
PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion RecognitionCode1
Self-supervised Learning for ECG-based Emotion RecognitionCode1
BHAAV- A Text Corpus for Emotion Analysis from Hindi StoriesCode1
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
Emotionless: Privacy-Preserving Speech Analysis for Voice AssistantsCode1
EEG-Based Emotion Recognition Using Regularized Graph Neural NetworksCode1
Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in TextsCode1
HiGRU: Hierarchical Gated Recurrent Units for Utterance-level Emotion RecognitionCode1
Aff-Wild2: Extending the Aff-Wild Database for Affect RecognitionCode1
Survey on Emotional Body Gesture RecognitionCode1
How Deep Neural Networks Can Improve Emotion Recognition on Video DataCode1
Training Deep Neural Networks on Noisy Labels with BootstrappingCode1
Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in ConversationCode0
Camera-based implicit mind reading by capturing higher-order semantic dynamics of human gaze within environmental context—0
A Robust Incomplete Multimodal Low-Rank Adaptation Approach for Emotion Recognition—0
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
CAST-Phys: Contactless Affective States Through Physiological signals Database—0
How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models?—0
Emotion Detection on User Front-Facing App Interfaces for Enhanced Schedule Optimization: A Machine Learning Approach—0
MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition—0
Reading Smiles: Proxy Bias in Foundation Models for Facial Emotion Recognition—0
Infant Cry Emotion Recognition Using Improved ECAPA-TDNN with Multiscale Feature Fusion and Attention EnhancementCode0
Deciphering Emotions in Children Storybooks: A Comparative Analysis of Multimodal LLMs in Educational Applications—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