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 1101–1125 of 2041 papers

TitleStatusHype
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning—0
TamilEmo: Finegrained Emotion Detection Dataset for Tamil—0
CALM: Contrastive Aligned Audio-Language Multirate and Multimodal Representations—0
Speech Emotion Recognition using Self-Supervised Features—0
LEAPMood: Light and Efficient Architecture to Predict Mood with Genetic Algorithm driven Hyperparameter Tuning—0
Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated LearningCode1
Speaker Normalization for Self-supervised Speech Emotion Recognition—0
Interpretability for Multimodal Emotion Recognition using Concept Activation Vectors—0
Self-supervised Graphs for Audio Representation Learning with Limited Labeled DataCode0
A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation—0
Automated Feature Extraction on AsMap for Emotion Classification using EEG—0
"That's so cute!": The CARE Dataset for Affective Response Detection—0
Sentiment-Aware Automatic Speech Recognition pre-training for enhanced Speech Emotion Recognition—0
Self-attention fusion for audiovisual emotion recognition with incomplete dataCode1
Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis for Eyewear DevicesCode0
A Pre-trained Audio-Visual Transformer for Emotion Recognition—0
Unsupervised Personalization of an Emotion Recognition System: The Unique Properties of the Externalization of Valence in Speech—0
Towards a General Deep Feature Extractor for Facial Expression Recognition—0
A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis—0
Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion RecognitionCode1
Zombies Eat Brains, You are Safe: A Knowledge Infusion based Multitasking System for Sarcasm Detection in Meme—0
DialogueEIN: Emotional Interaction Network for Emotion Recognition in Conversations—0
A Novel Multi-Task Learning Method for Symbolic Music Emotion Recognition—0
Tailor Versatile Multi-modal Learning for Multi-label Emotion RecognitionCode1
A study on cross-corpus speech emotion recognition and data augmentation—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