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 1626–1650 of 2041 papers

TitleStatusHype
Interpretable Deep Neural Networks for Dimensional and Categorical Emotion Recognition in-the-wild—0
Emotion Generation and Recognition: A StarGAN Approach—0
Facial Emotion Recognition using Convolutional Neural Networks—0
Conversational Transfer Learning for Emotion Recognition—0
A Deep Learning Based Chatbot for Campus Psychological Therapy—0
BHAAV- A Text Corpus for Emotion Analysis from Hindi StoriesCode1
Linking emotions to behaviors through deep transfer learningCode0
Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset—0
Automatic Group Cohesiveness Detection With Multi-modal Features—0
Emotion Recognition with Spatial Attention and Temporal Softmax Pooling—0
Zero-Shot Emotion Recognition via Affective Structural Embedding—0
Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace—0
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data BiasCode0
Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use CasesCode0
Student Engagement Detection Using Emotion Analysis, Eye Tracking and Head Movement with Machine LearningCode0
The emotions that we perceive in music: the influence of language and lyrics comprehension on agreement—0
EEG based Emotion Recognition of Image Stimuli—0
PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion RegressionCode0
HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for ElectroencephalographyCode0
Multimodal Embeddings from Language ModelsCode0
Learning Alignment for Multimodal Emotion Recognition from SpeechCode0
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning—0
Sentiment and Emotion Based Representations for Fake Reviews Detection—0
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
Emotion Recognition in Low-Resource Settings: An Evaluation of Automatic Feature Selection Methods—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