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 1751–1775 of 2041 papers

TitleStatusHype
Multimodal Speech Emotion Recognition Using Audio and TextCode0
DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful TechniquesCode0
Text-based Sentiment Analysis and Music Emotion Recognition—0
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in ConversationsCode0
BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion ClassificationCode0
USI-IR at IEST 2018: Sequence Modeling and Pseudo-Relevance Feedback for Implicit Emotion Detection—0
NL-FIIT at IEST-2018: Emotion Recognition utilizing Neural Networks and Multi-level PreprocessingCode0
UTFPR at IEST 2018: Exploring Character-to-Word Composition for Emotion Analysis—0
SINAI at IEST 2018: Neural Encoding of Emotional External Knowledge for Emotion Classification—0
HUMIR at IEST-2018: Lexicon-Sensitive and Left-Right Context-Sensitive BiLSTM for Implicit Emotion Recognition—0
HGSGNLP at IEST 2018: An Ensemble of Machine Learning and Deep Neural Architectures for Implicit Emotion Classification in Tweets—0
Leveraging Writing Systems Change for Deep Learning Based Chinese Emotion Analysis—0
Multi-Modal Sequence Fusion via Recursive Attention for Emotion Recognition—0
Interpretable Emoji Prediction via Label-Wise Attention LSTMs—0
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection—0
Fine-Grained Emotion Detection in Health-Related Online Posts—0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
Joint Learning for Emotion Classification and Emotion Cause Detection—0
Entropy-Assisted Multi-Modal Emotion Recognition Framework Based on Physiological Signals—0
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion RecognitionCode0
Convolutional Neural Network Approach for EEG-based Emotion Recognition using Brain Connectivity and its Spatial Information—0
Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm—0
Label-less Learning for Traffic Control in an Edge Network—0
EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction—0
Finding Good Representations of Emotions for Text Classification—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