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 501–525 of 2041 papers

TitleStatusHype
Exploiting Pseudo Future Contexts for Emotion Recognition in ConversationsCode0
An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated VideosCode0
Exploring Multilingual Unseen Speaker Emotion Recognition: Leveraging Co-Attention Cues in Multitask LearningCode0
Attentive Modality Hopping Mechanism for Speech Emotion RecognitionCode0
Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech ProcessingCode0
An Emotion Recognition Embedded System using a Lightweight Deep Learning ModelCode0
Explaining Deep Learning Embeddings for Speech Emotion Recognition by Predicting Interpretable Acoustic FeaturesCode0
DeepEmo: Learning and Enriching Pattern-Based Emotion RepresentationsCode0
ExHuBERT: Enhancing HuBERT Through Block Extension and Fine-Tuning on 37 Emotion DatasetsCode0
Explaining (Sarcastic) Utterances to Enhance Affect Understanding in Multimodal DialoguesCode0
Exploiting Multiple EEG Data Domains with Adversarial LearningCode0
Evaluating Gammatone Frequency Cepstral Coefficients with Neural Networks for Emotion Recognition from SpeechCode0
Evaluation Metrics for Automated Typographic Poster GenerationCode0
An audiovisual and contextual approach for categorical and continuous emotion recognition in-the-wildCode0
Enrolment-based personalisation for improving individual-level fairness in speech emotion recognitionCode0
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural AnnotatorsCode0
Enhancing Affective Representations of Music-Induced EEG through Multimodal Supervision and latent Domain AdaptationCode0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
An Attention Model for group-level emotion recognitionCode0
End-To-End Label Uncertainty Modeling for Speech-based Arousal Recognition Using Bayesian Neural NetworksCode0
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsCode0
End-to-End Label Uncertainty Modeling in Speech Emotion Recognition using Bayesian Neural Networks and Label Distribution LearningCode0
BERSting at the Screams: A Benchmark for Distanced, Emotional and Shouted Speech RecognitionCode0
EmotionX-IDEA: Emotion BERT -- an Affectional Model for ConversationCode0
EmotionX-KU: BERT-Max based Contextual Emotion ClassifierCode0
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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