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 1426–1450 of 2041 papers

TitleStatusHype
Developing emotion recognition for video conference software to support people with autism—0
Expression Recognition Analysis in the Wild—0
Analysis of Basic Emotions in Texts Based on BERT Vector Representation—0
4D Attention-based Neural Network for EEG Emotion Recognition—0
Fast Facial Landmark Detection and Applications: A Survey—0
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classificationCode0
Combining deep and unsupervised features for multilingual speech emotion recognitionCode0
Fixed-MAML for Few Shot Classification in Multilingual Speech Emotion RecognitionCode0
Facial Expressions Recognition System Using FPGA-Based Convolutional Neural NetworkCode0
A novel policy for pre-trained Deep Reinforcement Learning for Speech Emotion RecognitionCode0
Audio Content Analysis—0
Sensory Resilience based on Synesthesia—0
HisNet: A Polarity Lexicon based on WordNet for Emotion Analysis—0
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition—0
Unsupervised Cross-Lingual Speech Emotion Recognition Using DomainAdversarial Neural Network—0
Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study—0
Spontaneous Emotion Recognition from Facial Thermal Images—0
Exploring Deep Neural Networks and Transfer Learning for Analyzing Emotions in Tweets—0
Multi-Classifier Interactive Learning for Ambiguous Speech Emotion Recognition—0
3D-CNN for Facial Emotion Recognition in Videos—0
FERNet: Fine-grained Extraction and Reasoning Network for Emotion Recognition in Dialogues—0
Towards Label-Agnostic Emotion Embeddings—0
Convolutional and Recurrent Neural Networks for Spoken Emotion Recognition—0
Annotated Corpus of Tweets in English from Various Domains for Emotion Detection—0
Hitachi at SemEval-2020 Task 8: Simple but Effective Modality Ensemble for Meme Emotion Recognition—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