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 1701–1725 of 2041 papers

TitleStatusHype
Personalization of Affective Models to Enable Neuropsychiatric Digital Precision Health Interventions: A Feasibility Study—0
Personalized Adaptation with Pre-trained Speech Encoders for Continuous Emotion Recognition—0
Personalized Emotion Detection from Floor Vibrations Induced by Footsteps—0
Personalized Speech Emotion Recognition in Human-Robot Interaction using Vision Transformers—0
Photorealistic Facial Expression Synthesis by the Conditional Difference Adversarial Autoencoder—0
Pitch-Synchronous Single Frequency Filtering Spectrogram for Speech Emotion Recognition—0
Pose-based Body Language Recognition for Emotion and Psychiatric Symptom Interpretation—0
Positional-Spectral-Temporal Attention in 3D Convolutional Neural Networks for EEG Emotion Recognition—0
Towards Explainable, Privacy-Preserved Human-Motion Affect Recognition—0
Pre-trained Model Representations and their Robustness against Noise for Speech Emotion Analysis—0
Prior Aided Streaming Network for Multi-task Affective Recognitionat the 2nd ABAW2 Competition—0
Prior versus Contextual Emotion of a Word in a Sentence—0
Privacy against Real-Time Speech Emotion Detection via Acoustic Adversarial Evasion of Machine Learning—0
Privacy-preserving Representation Learning for Speech Understanding—0
Privacy-Preserving Video Classification with Convolutional Neural Networks—0
Private Speech Classification with Secure Multiparty Computation—0
Probing Speech Emotion Recognition Transformers for Linguistic Knowledge—0
Progressive Graph Convolution Network for EEG Emotion Recognition—0
Progressive Modality Reinforcement for Human Multimodal Emotion Recognition From Unaligned Multimodal Sequences—0
Progressive Residual Extraction based Pre-training for Speech Representation Learning—0
Prompting Audios Using Acoustic Properties For Emotion Representation—0
Prosodic Structure Beyond Lexical Content: A Study of Self-Supervised Learning—0
PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition—0
PsyCounAssist: A Full-Cycle AI-Powered Psychological Counseling Assistant System—0
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis—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