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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 701–750 of 2041 papers

TitleStatusHype
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation—0
Deep CNN with late fusion for realtime multimodal emotion recognition—0
Joint Contrastive Learning with Feature Alignment for Cross-Corpus EEG-based Emotion Recognition—0
Customising General Large Language Models for Specialised Emotion Recognition TasksCode0
Improving Personalisation in Valence and Arousal Prediction using Data Augmentation—0
AIMDiT: Modality Augmentation and Interaction via Multimodal Dimension Transformation for Emotion Recognition in Conversations—0
Multimodal Emotion Recognition by Fusing Video Semantic in MOOC Learning Scenarios—0
The Power of Properties: Uncovering the Influential Factors in Emotion Classification—0
What is Learnt by the LEArnable Front-end (LEAF)? Adapting Per-Channel Energy Normalisation (PCEN) to Noisy ConditionsCode0
Dynamic Resolution Guidance for Facial Expression Recognition—0
nEMO: Dataset of Emotional Speech in PolishCode0
Improving Facial Landmark Detection Accuracy and Efficiency with Knowledge Distillation—0
Towards Bi-Hemispheric Emotion Mapping through EEG: A Dual-Stream Neural Network Approach—0
IITK at SemEval-2024 Task 10: Who is the speaker? Improving Emotion Recognition and Flip Reasoning in Conversations via Speaker Embeddings—0
Music Recommendation Based on Facial Emotion Recognition—0
Exploring Emotions in Multi-componential Space using Interactive VR Games—0
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in ConversationCode0
Automated Assessment of Encouragement and Warmth in Classrooms Leveraging Multimodal Emotional Features and ChatGPT—0
Heterogeneity over Homogeneity: Investigating Multilingual Speech Pre-Trained Models for Detecting Audio DeepfakeCode0
Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages—0
UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause—0
Inclusive Design Insights from a Preliminary Image-Based Conversational Search Systems Evaluation—0
Cross-Attention is Not Always Needed: Dynamic Cross-Attention for Audio-Visual Dimensional Emotion Recognition—0
MMCert: Provable Defense against Adversarial Attacks to Multi-modal ModelsCode0
Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learning—0
Fusion approaches for emotion recognition from speech using acoustic and text-based features—0
The Strong Pull of Prior Knowledge in Large Language Models and Its Impact on Emotion Recognition—0
Emotion Recognition from the perspective of Activity Recognition—0
Unlocking the Emotional States of High-Risk Suicide Callers through Speech AnalysisCode0
The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data—0
Emotion Recognition Using Transformers with Masked LearningCode0
SUN Team's Contribution to ABAW 2024 Competition: Audio-visual Valence-Arousal Estimation and Expression Recognition—0
Audio-Visual Compound Expression Recognition Method based on Late Modality Fusion and Rule-based Decision—0
Boosting Continuous Emotion Recognition with Self-Pretraining using Masked Autoencoders, Temporal Convolutional Networks, and Transformers—0
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
Human Pose Descriptions and Subject-Focused Attention for Improved Zero-Shot Transfer in Human-Centric Classification Tasks—0
Group Movie Selection using Multi-channel Emotion Recognition—0
Robust Emotion Recognition in Context Debiasing—0
Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey—0
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
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
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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