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 801–825 of 2041 papers

TitleStatusHype
Emotion Recognition Using Wearables: A Systematic Literature Review Work in progress—0
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems—0
Empathetic Conversational Agents: Utilizing Neural and Physiological Signals for Enhanced Empathetic Interactions—0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation—0
Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models—0
Empathy Through Multimodality in Conversational Interfaces—0
Emotion Recognition Using Speaker Cues—0
Empirical Interpretation of Speech Emotion Perception with Attention Based Model for Speech Emotion Recognition—0
Empirical Interpretation of the Relationship Between Speech Acoustic Context and Emotion Recognition—0
Empowering Dysarthric Speech: Leveraging Advanced LLMs for Accurate Speech Correction and Multimodal Emotion Analysis—0
Emotion Recognition using Machine Learning and ECG signals—0
Emotion Recognition Using Fusion of Audio and Video Features—0
A Peek at Peak Emotion Recognition—0
End-to-End Continuous Speech Emotion Recognition in Real-life Customer Service Call Center Conversations—0
End-to-End Emotional Speech Synthesis Using Style Tokens and Semi-Supervised Training—0
End-to-end facial and physiological model for Affective Computing and applications—0
A hierarchical approach with feature selection for emotion recognition from speech—0
Emotion Recognition Using Convolutional Neural Networks—0
Emotion Recognition Using Convolutional Neural Network with Selected Statistical Photoplethysmogram Features—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—0
End-to-end transfer learning for speaker-independent cross-language and cross-corpus speech emotion recognition—0
Emotion Recognition under Consideration of the Emotion Component Process Model—0
Emotion recognition techniques with rule based and machine learning approaches—0
Comparison of Gender- and Speaker-adaptive Emotion Recognition—0
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System—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