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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1651–1700 of 2041 papers

TitleStatusHype
Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning—0
EmotionX-IDEA: Emotion BERT -- an Affectional Model for ConversationCode0
Context-Aware Emotion Recognition NetworksCode0
Multimodal Emotion Recognition Using Deep Canonical Correlation AnalysisCode0
User independent Emotion Recognition with Residual Signal-Image Network—0
Emotionless: Privacy-Preserving Speech Analysis for Voice AssistantsCode1
Pitch-Synchronous Single Frequency Filtering Spectrogram for Speech Emotion Recognition—0
Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning—0
Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets—0
EmoBed: Strengthening Monomodal Emotion Recognition via Training with Crossmodal Emotion Embeddings—0
Deep Temporal Analysis for Non-Acted Body Affect Recognition—0
EEG-Based Emotion Recognition Using Regularized Graph Neural NetworksCode1
Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion AnalysisCode0
AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition—0
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features—0
Attending to Emotional NarrativesCode0
Multimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition—0
EmotionX-KU: BERT-Max based Contextual Emotion ClassifierCode0
End-to-End Emotional Speech Synthesis Using Style Tokens and Semi-Supervised Training—0
Emotion Recognition Using Fusion of Audio and Video Features—0
Multimodal and Multi-view Models for Emotion Recognition—0
Learning Discriminative features using Center Loss and Reconstruction as Regularizer for Speech Emotion Recognition—0
Identifying Emotions from Walking using Affective and Deep Features—0
Factorized Higher-Order CNNs with an Application to Spatio-Temporal Emotion Estimation—0
Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition—0
Deep Learning based Emotion Recognition System Using Speech Features and TranscriptionsCode0
Feature-level and Model-level Audiovisual Fusion for Emotion Recognition in the Wild—0
Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in TextsCode1
THU\_NGN at SemEval-2019 Task 3: Dialog Emotion Classification using Attentional LSTM-CNN—0
KSU at SemEval-2019 Task 3: Hybrid Features for Emotion Recognition in Textual Conversation—0
ParallelDots at SemEval-2019 Task 3: Domain Adaptation with feature embeddings for Contextual Emotion Analysis—0
Facial Emotion Distribution Learning by Exploiting Low-Rank Label Correlations Locally—0
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English—0
A New Multilabel System for Automatic Music Emotion Recognition—0
Two-level Explanations in Music Emotion Recognition—0
EEG Classification by factoring in Sensor Configuration—0
Oculum afficit: Ocular Affect Recognition—0
Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis—0
Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis—0
A Novel Bi-hemispheric Discrepancy Model for EEG Emotion Recognition—0
Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances—0
Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal NetworksCode0
Group Emotion Recognition Using Machine Learning—0
A new model for the implementation of positive and negative emotion recognition—0
Automatic Emotion Recognition (AER) System based on Two-Level Ensemble of Lightweight Deep CNN Models—0
Human-Centered Emotion Recognition in Animated GIFsCode0
A Self-Attentive Emotion Recognition NetworkCode0
Speech Emotion Recognition Using Multi-hop Attention MechanismCode0
A Personalized Affective Memory Neural Model for Improving Emotion Recognition—0
An Interaction-aware Attention Network for Speech Emotion Recognition in Spoken DialogsCode0
Show:102550
← PrevPage 34 of 41Next →
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