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
Developing emotion recognition for video conference software to support people with autism—0
DialogueBERT: A Self-Supervised Learning based Dialogue Pre-training Encoder—0
DialogueEIN: Emotional Interaction Network for Emotion Recognition in Conversations—0
DialogueEIN: Emotion Interaction Network for Dialogue Affective Analysis—0
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation—0
Dimensional emotion recognition using visual and textual cues—0
Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction—0
Discovering Emotion and Reasoning its Flip in Multi-Party Conversations using Masked Memory Network and Transformer—0
Discriminating Neutral and Emotional Speech using Neural Networks—0
Discriminative Multiple Canonical Correlation Analysis for Information Fusion—0
Discriminative training for Convolved Multiple-Output Gaussian processes—0
Disentangling Prosody Representations with Unsupervised Speech Reconstruction—0
Distributed Processing of Biosignal-Database for Emotion Recognition with Mahout—0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study—0
Divergent Emotional Patterns in Disinformation on Social Media? An Analysis of Tweets and TikToks about the DANA in Valencia—0
Divide-and-Conquer based Ensemble to Spot Emotions in Speech using MFCC and Random Forest—0
DMGroup at EmoInt-2017: Emotion Intensity Using Ensemble Method—0
DNN-HMM based Speaker Adaptive Emotion Recognition using Proposed Epoch and MFCC Features—0
Do Deep Neural Networks Forget Facial Action Units? -- Exploring the Effects of Transfer Learning in Health Related Facial Expression Recognition—0
Does Visual Self-Supervision Improve Learning of Speech Representations for Emotion Recognition?—0
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions—0
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition—0
Domain Adversarial for Acoustic Emotion Recognition—0
Domain adversarial learning for emotion recognition—0
Do Multimodal Emotion Recognition Models Tackle Ambiguity?—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