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 1551–1575 of 2041 papers

TitleStatusHype
Atom Search Optimization with Simulated Annealing -- a Hybrid Metaheuristic Approach for Feature Selection—0
Does Visual Self-Supervision Improve Learning of Speech Representations for Emotion Recognition?—0
An Event-comment Social Media Corpus for Implicit Emotion Analysis—0
An Algerian Corpus and an Annotation Platform for Opinion and Emotion Analysis—0
IIIT-H TEMD Semi-Natural Emotional Speech Database from Professional Actors and Non-Actors—0
Improving Sentiment Analysis with Biofeedback Data—0
Speech-Emotion Detection in an Indonesian Movie—0
Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition—0
Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training—0
A Spontaneous Driver Emotion Facial Expression (DEFE) Dataset for Intelligent Vehicles—0
How to read faces without looking at them—0
A Wearable Social Interaction Aid for Children with Autism—0
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition—0
On The Differences Between Song and Speech Emotion Recognition: Effect of Feature Sets, Feature Types, and ClassifiersCode0
Joint Deep Cross-Domain Transfer Learning for Emotion Recognition—0
Cross Lingual Cross Corpus Speech Emotion Recognition—0
EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege's Principle—0
Emotion Recognition From Gait Analyses: Current Research and Future Directions—0
Deep Neural Networks for Automatic Speech Processing: A Survey from Large Corpora to Limited Data—0
Guided Generative Adversarial Neural Network for Representation Learning and High Fidelity Audio Generation using Fewer Labelled Audio Data—0
Emotion Recognition System from Speech and Visual Information based on Convolutional Neural Networks—0
Multitask Learning and Multistage Fusion for Dimensional Audiovisual Emotion RecognitionCode0
Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks—0
A Comparative Study of Western and Chinese Classical Music based on Soundscape Models—0
Emotion Recognition for In-the-wild Videos—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