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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 851–875 of 2041 papers

TitleStatusHype
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors—0
Comparison of Gender- and Speaker-adaptive Emotion Recognition—0
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System—0
Ethics Sheets for AI Tasks—0
Emotion Recognition System from Speech and Visual Information based on Convolutional Neural Networks—0
Comparison and Analysis of Deep Audio Embeddings for Music Emotion Recognition—0
A Parallel Corpus of Music and Lyrics Annotated with Emotions—0
A Heterogeneous Multimodal Graph Learning Framework for Recognizing User Emotions in Social Networks—0
Acquiring a Dictionary of Emotion-Provoking Events—0
A breakthrough in Speech emotion recognition using Deep Retinal Convolution Neural Networks—0
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos—0
ELP-Adapters: Parameter Efficient Adapter Tuning for Various Speech Processing Tasks—0
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild—0
Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition—0
Evaluation of Speaker Anonymization on Emotional Speech—0
Event Based Emotion Classification for News Articles—0
EventFormer: AU Event Transformer for Facial Action Unit Event Detection—0
EvoFA: Evolvable Fast Adaptation for EEG Emotion Recognition—0
EVOKE: Emotion Enabled Virtual Avatar Mapping Using Optimized Knowledge Distillation—0
Comparative Study of Pre-Trained BERT Models for Code-Mixed Hindi-English Data—0
Emotion Recognition In Persian Speech Using Deep Neural Networks—0
Emotion Recognition in Low-Resource Settings: An Evaluation of Automatic Feature Selection Methods—0
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition—0
Emotion Recognition in Conversation using Probabilistic Soft Logic—0
ComFace: Facial Representation Learning with Synthetic Data for Comparing Faces—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