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 1601–1625 of 2041 papers

TitleStatusHype
A study on cross-corpus speech emotion recognition and data augmentation—0
A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis—0
A Study on Using Transfer Learning to Improve BERT Model for Emotional Classification of Chinese Lyrics—0
A Survey of Deep Learning for Group-level Emotion Recognition—0
A survey of smart classroom: Concept, technologies and facial emotions recognition application—0
A Survey on Paralinguistics in Tamil Speech Processing—0
A Survey on Physiological Signal Based Emotion Recognition—0
A Survey on Sentiment and Emotion Analysis for Computational Literary Studies—0
A Survey on Speech Large Language Models—0
A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future Directions—0
A Time Series Analysis of Emotional Loading in Central Bank Statements—0
Atom Search Optimization with Simulated Annealing -- a Hybrid Metaheuristic Approach for Feature Selection—0
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
A Transformer Architecture for Stress Detection from ECG—0
Attention-based Region of Interest (ROI) Detection for Speech Emotion Recognition—0
Attention Driven Fusion for Multi-Modal Emotion Recognition—0
Attentive Convolutional Neural Network based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech—0
Attentive Cross-modal Connections for Deep Multimodal Wearable-based Emotion Recognition—0
Attributes-aware Visual Emotion Representation Learning—0
AttX: Attentive Cross-Connections for Fusion of Wearable Signals in Emotion Recognition—0
A Two-Stage Efficient 3-D CNN Framework for EEG Based Emotion Recognition—0
A Two-Stage Multimodal Emotion Recognition Model Based on Graph Contrastive Learning—0
audEERING's approach to the One-Minute-Gradual Emotion Challenge—0
Audio Content Analysis—0
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance—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