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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 126–150 of 2041 papers

TitleStatusHype
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective ComputingCode1
EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion RecognitionCode1
EmoNeXt: an Adapted ConvNeXt for Facial Emotion RecognitionCode1
Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG SignalsCode1
A vector quantized masked autoencoder for speech emotion recognitionCode1
EmoGator: A New Open Source Vocal Burst Dataset with Baseline Machine Learning Classification MethodologiesCode1
EmoSpeech: Guiding FastSpeech2 Towards Emotional Text to SpeechCode1
emoDARTS: Joint Optimisation of CNN & Sequential Neural Network Architectures for Superior Speech Emotion RecognitionCode1
Continuous Emotion Recognition with Audio-visual Leader-follower Attentive FusionCode1
Emo-DNA: Emotion Decoupling and Alignment Learning for Cross-Corpus Speech Emotion RecognitionCode1
EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTaCode1
A Transformer-based joint-encoding for Emotion Recognition and Sentiment AnalysisCode1
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in ConversationsCode1
Audio-Visual Fusion for Emotion Recognition in the Valence-Arousal Space Using Joint Cross-AttentionCode1
EmoDynamiX: Emotional Support Dialogue Strategy Prediction by Modelling MiXed Emotions and Discourse DynamicsCode1
EEG-Based Emotion Recognition Using Genetic Algorithm Optimized Multi-Layer PerceptronCode1
EEG-Based Emotion Recognition Using Regularized Graph Neural NetworksCode1
EEGMatch: Learning with Incomplete Labels for Semi-Supervised EEG-based Cross-Subject Emotion RecognitionCode1
A Supervised Information Enhanced Multi-Granularity Contrastive Learning Framework for EEG Based Emotion RecognitionCode1
BHAAV- A Text Corpus for Emotion Analysis from Hindi StoriesCode1
ECPE-2D: Emotion-Cause Pair Extraction based on Joint Two-Dimensional Representation, Interaction and PredictionCode1
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning SettingsCode1
EfficientFER: EfficientNetv2 Based Deep Learning Approach for Facial Expression RecognitionCode1
A proposal for Multimodal Emotion Recognition using aural transformers and Action Units on RAVDESS datasetCode1
A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text CorporaCode1
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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