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 501–525 of 2041 papers

TitleStatusHype
Decoding Human Emotions: Analyzing Multi-Channel EEG Data using LSTM Networks—0
Computationally Efficient Wasserstein Loss for Structured Labels—0
Addressing Racial Bias in Facial Emotion Recognition—0
Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition—0
APEX: Attention on Personality based Emotion ReXgnition Framework—0
Deep Convolution Network Based Emotion Analysis for Automatic Detection of Mild Cognitive Impairment in the Elderly—0
Computational Emotion Analysis From Images: Recent Advances and Future Directions—0
A Multimodal Emotion Recognition System: Integrating Facial Expressions, Body Movement, Speech, and Spoken Language—0
AttX: Attentive Cross-Connections for Fusion of Wearable Signals in Emotion Recognition—0
Deep Evolution for Facial Emotion Recognition—0
Compound Expression Recognition via Large Vision-Language Models—0
A Cross-Corpus Speech Emotion Recognition Method Based on Supervised Contrastive Learning—0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation—0
A Peek at Peak Emotion Recognition—0
A hierarchical approach with feature selection for emotion recognition from speech—0
A breakthrough in Speech emotion recognition using Deep Retinal Convolution Neural Networks—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—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
A Parallel Corpus of Music and Lyrics Annotated with Emotions—0
Comparison and Analysis of Deep Audio Embeddings for Music Emotion Recognition—0
A Heterogeneous Multimodal Graph Learning Framework for Recognizing User Emotions in Social Networks—0
Acquiring a Dictionary of Emotion-Provoking Events—0
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos—0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study—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