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 1276–1300 of 2041 papers

TitleStatusHype
Dual-GAN: Joint BVP and Noise Modeling for Remote Physiological Measurement—0
Learning a Facial Expression Embedding Disentangled From Identity—0
Multi-Task Learning and Adapted Knowledge Models for Emotion-Cause Extraction—0
Best Practices for Noise-Based Augmentation to Improve the Performance of Deployable Speech-Based Emotion Recognition Systems—0
SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model—0
Silent Speech and Emotion Recognition from Vocal Tract Shape Dynamics in Real-Time MRI—0
Automatic Analysis of the Emotional Content of Speech in Daylong Child-Centered Recordings from a Neonatal Intensive Care Unit—0
Tracing Back Music Emotion Predictions to Sound Sources and Intuitive Perceptual QualitiesCode1
Efficient Speech Emotion Recognition Using Multi-Scale CNN and AttentionCode1
Subject Independent Emotion Recognition using EEG Signals Employing Attention Driven Neural Networks—0
An Attribute-Aligned Strategy for Learning Speech Representation—0
Musical Prosody-Driven Emotion Classification: Interpreting Vocalists Portrayal of Emotions Through Machine Learning—0
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in ConversationsCode1
EmoDNN: Understanding emotions from short texts through a deep neural network ensemble—0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation—0
Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter—0
Learning Paralinguistic Features from Audiobooks through Style Voice Conversion—0
An Architecture for Accelerated Large-Scale Inference of Transformer-Based Language Models—0
WRIME: A New Dataset for Emotional Intensity Estimation with Subjective and Objective AnnotationsCode1
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
Emotion Recognition in Horses with Convolutional Neural NetworksCode0
Speech & Song Emotion Recognition Using Multilayer Perceptron and Standard Vector Machine—0
MUSER: MUltimodal Stress Detection using Emotion Recognition as an Auxiliary Task—0
Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the WildCode1
Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation—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