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 1401–1425 of 2041 papers

TitleStatusHype
Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition—0
Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language ModelsCode0
A Discriminative Vectorial Framework for Multi-modal Feature Representation—0
An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions—0
Analyzing the Influence of Dataset Composition for Emotion Recognition—0
Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games—0
Investigations on Audiovisual Emotion Recognition in Noisy Conditions—0
Computationally Efficient Wasserstein Loss for Structured Labels—0
Emotion pattern detection on facial videos using functional statistics—0
The Labeled Multiple Canonical Correlation Analysis for Information Fusion—0
Emotion recognition techniques with rule based and machine learning approaches—0
Discriminative Multiple Canonical Correlation Analysis for Information Fusion—0
Towards Emotion Recognition in Hindi-English Code-Mixed Data: A Transformer Based ApproachCode0
Contrastive Unsupervised Learning for Speech Emotion Recognition—0
Lie-Sensor: A Live Emotion Verifier or a Licensor for Chat Applications using Emotional Intelligence—0
CASA-Based Speaker Identification Using Cascaded GMM-CNN Classifier in Noisy and Emotional Talking Conditions—0
Non-linear frequency warping using constant-Q transformation for speech emotion recognition—0
EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG with An Application to Emotion Recognition—0
ScalingNet: extracting features from raw EEG data for emotion recognition—0
Privacy-Preserving Video Classification with Convolutional Neural Networks—0
Multi-Task Self-Supervised Pre-Training for Music Classification—0
Speech Emotion Recognition with Multiscale Area Attention and Data Augmentation—0
HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognition—0
Neural Network architectures to classify emotions in Indian Classical Music—0
FOIT: Fast Online Instance Transfer for Improved EEG Emotion RecognitionCode0
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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