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 901–925 of 2041 papers

TitleStatusHype
Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition—0
Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion MiningCode0
"We care": Improving Code Mixed Speech Emotion Recognition in Customer-Care Conversations—0
Capturing Spectral and Long-term Contextual Information for Speech Emotion Recognition Using Deep Learning Techniques—0
Contextual Emotion Recognition Using Transformer-Based ModelsCode0
Using Scene and Semantic Features for Multi-modal Emotion Recognition—0
Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion—0
FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion RecognitionCode0
Self-Supervised Learning for Audio-Based Emotion Recognition—0
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality ConversionCode0
Cross-Corpus Multilingual Speech Emotion Recognition: Amharic vs. Other Languages—0
Unveiling Emotions from EEG: A GRU-Based Approach—0
MASR: Multi-label Aware Speech Representation—0
Emotional Intelligence of Large Language Models—0
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection—0
EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributes—0
Emotion recognition based on multi-modal electrophysiology multi-head attention Contrastive Learning—0
Emotion Analysis on EEG Signal Using Machine Learning and Neural Network—0
Evaluating raw waveforms with deep learning frameworks for speech emotion recognition—0
A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition—0
SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images—0
Human Emotion Recognition Based On Galvanic Skin Response signal Feature Selection and SVM—0
A Dual-Stream Recurrence-Attention Network With Global-Local Awareness for Emotion Recognition in Textual Dialog—0
Empirical Interpretation of the Relationship Between Speech Acoustic Context and Emotion Recognition—0
Emotion Analysis of Tweets Banning Education in Afghanistan—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