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 1501–1550 of 2041 papers

TitleStatusHype
Cross-individual Recognition of Emotions by a Dynamic Entropy based on Pattern Learning with EEG features—0
Attention Driven Fusion for Multi-Modal Emotion Recognition—0
Exploiting Vietnamese Social Media Characteristics for Textual Emotion Recognition in Vietnamese—0
The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data—0
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition—0
Learning Emotional-Blinded Face Representations—0
Optimizing Speech Emotion Recognition using Manta-Ray Based Feature Selection—0
Group-Level Emotion Recognition Using a Unimodal Privacy-Safe Non-Individual Approach—0
Multi-modal embeddings using multi-task learning for emotion recognition—0
Is Everything Fine, Grandma? Acoustic and Linguistic Modeling for Robust Elderly Speech Emotion RecognitionCode0
A Genetic Feature Selection Based Two-stream Neural Network for Anger Veracity Recognition—0
Fine-grained Early Frequency Attention for Deep Speaker Representation Learning—0
Convolutional Speech Recognition with Pitch and Voice Quality Features—0
Suspect AI: Vibraimage, Emotion Recognition Technology, and Algorithmic Opacity—0
Introducing Representations of Facial Affect in Automated Multimodal Deception Detection—0
Unsupervised Multi-Modal Representation Learning for Affective Computing with Multi-Corpus Wearable Data—0
EmoGraph: Capturing Emotion Correlations using Graph Networks—0
Emotion Carrier Recognition from Personal Narratives—0
Hey Human, If your Facial Emotions are Uncertain, You Should Use Bayesian Neural Networks!—0
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
The BIRAFFE2 Experiment. Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems—0
Variants of BERT, Random Forests and SVM approach for Multimodal Emotion-Target Sub-challenge—0
Emotion Correlation Mining Through Deep Learning Models on Natural Language Text—0
DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion AnalysisCode0
YNU-HPCC at SemEval-2020 Task 8: Using a Parallel-Channel Model for Memotion AnalysisCode0
HEU Emotion: A Large-scale Database for Multi-modal Emotion Recognition in the Wild—0
Generative Adversarial Stacked Autoencoders for Facial Pose Normalization and Emotion Recognition—0
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning—0
COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions AttributesCode0
Temporal aggregation of audio-visual modalities for emotion recognition—0
Low Rank Fusion based Transformers for Multimodal Sequences—0
Shallow over Deep Neural Networks: A empirical analysis for human emotion classification using audio data—0
Systematic Evaluation of a Framework for Unsupervised Emotion Recognition for Narrative Text—0
Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis—0
TRANSFER :- DEEP INDUCTIVE NETWORK FOR FACIAL EMOTION RECOGNITIONCode0
Private Speech Classification with Secure Multiparty Computation—0
Towards Emotion-aided Multi-modal Dialogue Act Classification—0
Contextualized Emotion Recognition in Conversation as Sequence Tagging—0
Meta Transfer Learning for Emotion Recognition—0
Manipulating emotions for ground truth emotion analysis—0
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply—0
Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech ProcessingCode0
Data Augmentation for Enhancing EEG-based Emotion Recognition with Deep Generative Models—0
A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition—0
Learning Visual Emotion Representations From Web Data—0
Emotion Recognition Using Convolutional Neural Network with Selected Statistical Photoplethysmogram Features—0
Impact of multiple modalities on emotion recognition: investigation into 3d facial landmarks, action units, and physiological data—0
Convolutional Neural Network for emotion recognition to assist psychiatrists and psychologists during the COVID-19 pandemic: experts opinion—0
ConcealNet: An End-to-end Neural Network for Packet Loss Concealment in Deep Speech Emotion Recognition—0
"I have vxxx bxx connexxxn!": Facing Packet Loss in Deep Speech Emotion Recognition—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