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 2001–2025 of 2041 papers

TitleStatusHype
Discriminating Neutral and Emotional Speech using Neural Networks—0
Hierarchical Sparse and Collaborative Low-Rank Representation for Emotion RecognitionCode0
Joint Emotion Analysis via Multi-task Gaussian Processes—0
Real-time emotion recognition for gaming using deep convolutional network featuresCode0
Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns—0
Generating a Word-Emotion Lexicon from \#Emotional Tweets—0
Improved Frame Level Features and SVM Supervectors Approach for the Recogniton of Emotional States from Speech: Application to categorical and dimensional states—0
Semantic Role Labeling of Emotions in Tweets—0
Depeche Mood: a Lexicon for Emotion Analysis from Crowd Annotated News—0
DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News—0
Speech-Based Emotion Recognition: Feature Selection by Self-Adaptive Multi-Criteria Genetic Algorithm—0
EMOVO Corpus: an Italian Emotional Speech Database—0
VOCE Corpus: Ecologically Collected Speech Annotated with Physiological and Psychological Stress Assessments—0
Construction and Annotation of a French Folkstale Corpus—0
Comparison of Gender- and Speaker-adaptive Emotion Recognition—0
Acquiring a Dictionary of Emotion-Provoking Events—0
Emotion Analysis Platform on Chinese Microblog—0
MFCC based Enlargement of the Training Set for Emotion Recognition in Speech—0
Real-time Automatic Emotion Recognition from Body Gestures—0
Dynamic Model of Facial Expression Recognition based on Eigen-face Approach—0
Construction of Emotional Lexicon Using Potts Model—0
General Purpose Textual Sentiment Analysis and Emotion Detection Tools—0
Linguistic Linked Data for Sentiment Analysis—0
Crowdsourcing a Word-Emotion Association Lexicon—0
Utterance-Level Multimodal Sentiment Analysis—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