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

Showing 13511375 of 2041 papers

TitleStatusHype
A Circular-Structured Representation for Visual Emotion Distribution Learning0
Learning a Facial Expression Embedding Disentangled From Identity0
Dual-GAN: Joint BVP and Noise Modeling for Remote Physiological Measurement0
Progressive Modality Reinforcement for Human Multimodal Emotion Recognition From Unaligned Multimodal Sequences0
Multi-Task Learning and Adapted Knowledge Models for Emotion-Cause Extraction0
SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model0
Best Practices for Noise-Based Augmentation to Improve the Performance of Deployable Speech-Based Emotion Recognition Systems0
Silent Speech and Emotion Recognition from Vocal Tract Shape Dynamics in Real-Time MRI0
Automatic Analysis of the Emotional Content of Speech in Daylong Child-Centered Recordings from a Neonatal Intensive Care Unit0
Subject Independent Emotion Recognition using EEG Signals Employing Attention Driven Neural Networks0
An Attribute-Aligned Strategy for Learning Speech Representation0
Musical Prosody-Driven Emotion Classification: Interpreting Vocalists Portrayal of Emotions Through Machine Learning0
EmoDNN: Understanding emotions from short texts through a deep neural network ensemble0
An Architecture for Accelerated Large-Scale Inference of Transformer-Based Language Models0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation0
Learning Paralinguistic Features from Audiobooks through Style Voice Conversion0
Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter0
Emotion Recognition in Horses with Convolutional Neural NetworksCode0
Speech & Song Emotion Recognition Using Multilayer Perceptron and Standard Vector Machine0
MUSER: MUltimodal Stress Detection using Emotion Recognition as an Auxiliary Task0
Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation0
Deep scattering network for speech emotion recognition0
Towards Explainable, Privacy-Preserved Human-Motion Affect Recognition0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study0
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1M2D-CLAPEmoA77.4Unverified
2M2D2EmoA76.7Unverified
3M2DEmoA76.1Unverified
4Jukebox (Pre-training: CALM)EmoA72.1Unverified
5CLMR (Pre-training: contrastive)EmoA67.8Unverified
#ModelMetricClaimedVerifiedStatus
1LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+AttentionAccuracy86.7Unverified
2MultiMAE-DERWAR83.61Unverified
3Intermediate-Attention-FusionAccuracy81.58Unverified
4Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedSTAccuracy80.08Unverified
5ERANN-0-4Accuracy74.8Unverified
#ModelMetricClaimedVerifiedStatus
1CAGETop-3 Accuracy (%)14.73Unverified
2FocusCLIPTop-3 Accuracy (%)13.73Unverified
#ModelMetricClaimedVerifiedStatus
1VGG based5-class test accuracy66.13Unverified
#ModelMetricClaimedVerifiedStatus
1MaSaC-ERC-ZF1-score (Weighted)51.17Unverified
#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy40.34Unverified
#ModelMetricClaimedVerifiedStatus
1w2v2-L-robust-12Concordance correlation coefficient (CCC)0.64Unverified
#ModelMetricClaimedVerifiedStatus
14D-aNNAccuracy96.1Unverified
#ModelMetricClaimedVerifiedStatus
1CNN1'"1Unverified