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 1826–1850 of 2041 papers

TitleStatusHype
Framewise approach in multimodal emotion recognition in OMG challenge—0
audEERING's approach to the One-Minute-Gradual Emotion Challenge—0
Dimensional emotion recognition using visual and textual cues—0
Multimodal Emotion Recognition for One-Minute-Gradual Emotion Challenge—0
A Multi-component CNN-RNN Approach for Dimensional Emotion Recognition in-the-wild—0
Transformer for Emotion RecognitionCode0
Multimodal Utterance-level Affect Analysis using Visual, Audio and Text FeaturesCode0
Classifier-based Polarity Propagation in a WordNet—0
A Vietnamese Dialog Act Corpus Based on ISO 24617-2 standard—0
EMTC: Multilabel Corpus in Movie Domain for Emotion Analysis in Conversational Text—0
Construction of English-French Multimodal Affective Conversational Corpus from TV Dramas—0
Contextual Dependencies in Time-Continuous Multidimensional Affect Recognition—0
Sentence and Clause Level Emotion Annotation, Detection, and Classification in a Multi-Genre Corpus—0
Understanding Emotions: A Dataset of Tweets to Study Interactions between Affect Categories—0
A Comparison Of Emotion Annotation Schemes And A New Annotated Data Set—0
WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art—0
Word Affect Intensities—0
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and BeyondCode0
Ladder Networks for Emotion Recognition: Using Unsupervised Auxiliary Tasks to Improve Predictions of Emotional Attributes—0
DeepEmo: Learning and Enriching Pattern-Based Emotion RepresentationsCode0
Siamese Generative Adversarial Privatizer for Biometric Data—0
I Know How You Feel: Emotion Recognition with Facial Landmarks—0
Domain Adversarial for Acoustic Emotion Recognition—0
Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep LearningCode0
On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks—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