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 1001–1025 of 2041 papers

TitleStatusHype
Capturing Spectral and Long-term Contextual Information for Speech Emotion Recognition Using Deep Learning Techniques—0
CASA-Based Speaker Identification Using Cascaded GMM-CNN Classifier in Noisy and Emotional Talking Conditions—0
Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition—0
CAST-Phys: Contactless Affective States Through Physiological signals Database—0
CAT: Credibility Analysis of Arabic Content on Twitter—0
CEFER: A Four Facets Framework based on Context and Emotion embedded features for Implicit and Explicit Emotion Recognition—0
CG-MER: A Card Game-based Multimodal dataset for Emotion Recognition—0
Characterizing Types of Convolution in Deep Convolutional Recurrent Neural Networks for Robust Speech Emotion Recognition—0
Chat-Capsule: A Hierarchical Capsule for Dialog-level Emotion Analysis—0
Churn Prediction via Multimodal Fusion Learning:Integrating Customer Financial Literacy, Voice, and Behavioral Data—0
CIT-EmotionNet: CNN Interactive Transformer Network for EEG Emotion Recognition—0
CKERC : Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation—0
Classifier-based Polarity Propagation in a WordNet—0
Classifying Emotional Utterances by Employing Multi-modal Speech Emotion Recognition—0
Classifying emotions and engagement in online learning based on a single facial expression recognition neural network—0
CLDTA: Contrastive Learning based on Diagonal Transformer Autoencoder for Cross-Dataset EEG Emotion Recognition—0
ClimaEmpact: Domain-Aligned Small Language Models and Datasets for Extreme Weather Analytics—0
Climate and Weather: Inspecting Depression Detection via Emotion Recognition—0
CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation—0
CN-HIT-MI.T at SemEval-2020 Task 8: Memotion Analysis Based on BERT—0
CNN based music emotion classification—0
CNN+LSTM Architecture for Speech Emotion Recognition with Data Augmentation—0
CNN-n-GRU: end-to-end speech emotion recognition from raw waveform signal using CNNs and gated recurrent unit networks—0
CocoER: Aligning Multi-Level Feature by Competition and Coordination for Emotion Recognition—0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation—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