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 1501–1525 of 2041 papers

TitleStatusHype
Contextualized Emotion Recognition in Conversation as Sequence Tagging—0
Private Speech Classification with Secure Multiparty Computation—0
Systematic Evaluation of a Framework for Unsupervised Emotion Recognition for Narrative Text—0
Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis—0
Towards Emotion-aided Multi-modal Dialogue Act Classification—0
ECPE-2D: Emotion-Cause Pair Extraction based on Joint Two-Dimensional Representation, Interaction and PredictionCode1
A Transformer-based joint-encoding for Emotion Recognition and Sentiment AnalysisCode1
Meta Transfer Learning for Emotion Recognition—0
Emotion Recognition on large video dataset based on Convolutional Feature Extractor and Recurrent Neural NetworkCode1
Manipulating emotions for ground truth emotion analysis—0
Emotion Recognition in Audio and Video Using Deep Neural NetworksCode1
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply—0
Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech ProcessingCode0
audino: A Modern Annotation Tool for Audio and SpeechCode2
Data Augmentation for Enhancing EEG-based Emotion Recognition with Deep Generative Models—0
A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition—0
Learning Visual Emotion Representations From Web Data—0
Emotion Recognition Using Convolutional Neural Network with Selected Statistical Photoplethysmogram Features—0
Impact of multiple modalities on emotion recognition: investigation into 3d facial landmarks, action units, and physiological data—0
Convolutional Neural Network for emotion recognition to assist psychiatrists and psychologists during the COVID-19 pandemic: experts opinion—0
ConcealNet: An End-to-end Neural Network for Packet Loss Concealment in Deep Speech Emotion Recognition—0
"I have vxxx bxx connexxxn!": Facing Packet Loss in Deep Speech Emotion Recognition—0
Learning and Evaluating Emotion Lexicons for 91 LanguagesCode1
Real-time Facial Expression Recognition "In The Wild'' by Disentangling 3D Expression from IdentityCode1
Atom Search Optimization with Simulated Annealing -- a Hybrid Metaheuristic Approach for Feature Selection—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