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 1326–1350 of 2041 papers

TitleStatusHype
Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition—0
Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability—0
A Survey on Paralinguistics in Tamil Speech Processing—0
A New View of Multi-modal Language Analysis: Audio and Video Features as Text ``Styles''—0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks—0
Enhancing Segment-Based Speech Emotion Recognition by Deep Self-Learning—0
User profile-driven large-scale multi-agent learning from demonstration in federated human-robot collaborative environments—0
Pre-training strategies and datasets for facial representation learningCode1
Convolutional Neural Network Hyperparameters optimization for Facial Emotion RecognitionCode0
Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition—0
Discovering Emotion and Reasoning its Flip in Multi-Party Conversations using Masked Memory Network and Transformer—0
Responsible AI: Gender bias assessment in emotion recognition—0
Computational Emotion Analysis From Images: Recent Advances and Future Directions—0
Multimodal End-to-End Sparse Model for Emotion RecognitionCode1
Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition—0
EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion RecognitionCode1
Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language ModelsCode0
A Discriminative Vectorial Framework for Multi-modal Feature Representation—0
Analyzing the Influence of Dataset Composition for Emotion Recognition—0
An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions—0
Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games—0
Morphset:Augmenting categorical emotion datasets with dimensional affect labels using face morphingCode1
Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion RecognitionCode1
Investigations on Audiovisual Emotion Recognition in Noisy Conditions—0
Computationally Efficient Wasserstein Loss for Structured Labels—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