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 501–525 of 2041 papers

TitleStatusHype
Joint Multimodal Transformer for Emotion Recognition in the WildCode1
DiTMoS: Delving into Diverse Tiny-Model Selection on MicrocontrollersCode0
A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Product—0
CKERC : Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation—0
Group Movie Selection using Multi-channel Emotion Recognition—0
Human Pose Descriptions and Subject-Focused Attention for Improved Zero-Shot Transfer in Human-Centric Classification Tasks—0
Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey—0
Robust Emotion Recognition in Context Debiasing—0
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective ComputingCode1
Speech Emotion Recognition Via CNN-Transformer and Multidimensional Attention MechanismCode1
Cultural-Aware AI Model for Emotion RecognitionCode0
Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition—0
Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion AttributionCode0
EMOVOME: A Dataset for Emotion Recognition in Spontaneous Real-Life SpeechCode0
Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future DirectionsCode0
Exploring the dynamic interplay of cognitive load and emotional arousal by using multimodal measurements: Correlation of pupil diameter and emotional arousal in emotionally engaging tasks—0
SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)Code0
Curriculum Learning Meets Directed Acyclic Graph for Multimodal Emotion RecognitionCode1
Emotional Voice Messages (EMOVOME) database: emotion recognition in spontaneous voice messages—0
EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams—0
ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion ModelingCode0
GiMeFive: Towards Interpretable Facial Emotion ClassificationCode1
The AffectToolbox: Affect Analysis for Everyone—0
EMO-SUPERB: An In-depth Look at Speech Emotion RecognitionCode2
Filter-based multi-task cross-corpus feature learning for speech emotion recognitionCode0
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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