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 1926–1950 of 2041 papers

TitleStatusHype
Emotional Voice Messages (EMOVOME) database: emotion recognition in spontaneous voice messages—0
Emotion analysis and detection during COVID-19—0
Emotion Analysis of Songs Based on Lyrical and Audio Features—0
Emotion Analysis of Tweets Banning Education in Afghanistan—0
Emotion Analysis on EEG Signal Using Machine Learning and Neural Network—0
Emotion Analysis on Twitter: The Hidden Challenge—0
Emotion Analysis Platform on Chinese Microblog—0
Emotion Analysis using Multi-Layered Networks for Graphical Representation of Tweets—0
Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learning—0
EmotionCaps: Enhancing Audio Captioning Through Emotion-Augmented Data Generation—0
Emotion Carrier Recognition from Personal Narratives—0
Emotion Classification of Children Expressions—0
Emotion controllable speech synthesis using emotion-unlabeled dataset with the assistance of cross-domain speech emotion recognition—0
Emotion Correlation Mining Through Deep Learning Models on Natural Language Text—0
Emotion Detection in Code-switching Texts via Bilingual and Sentimental Information—0
Emotion Detection in Reddit: Comparative Study of Machine Learning and Deep Learning Techniques—0
Emotion Detection on User Front-Facing App Interfaces for Enhanced Schedule Optimization: A Machine Learning Approach—0
Emotion Detection through Body Gesture and Face—0
Emotion Distribution Learning from Texts—0
Emotion Dynamics Modeling via BERT—0
Emotion Embeddings x2014 Learning Stable and Homogeneous Abstractions from Heterogeneous Affective Datasets—0
Automatic Emotion Experiencer Recognition—0
Emotion Generation and Recognition: A StarGAN Approach—0
Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis—0
Emotion in Code-switching Texts: Corpus Construction and 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