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Emotion Recognition
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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
논문
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Prosody-Enhanced Acoustic Pre-training and Acoustic-Disentangled Prosody Adapting for Movie Dubbing
United we stand, Divided we fall: Handling Weak Complementary Relationships for Audio-Visual Emotion Recognition in Valence-Arousal Space
Compound Expression Recognition via Large Vision-Language Models
Emotion Recognition with CLIP and Sequential Learning
Mamba-VA: A Mamba-based Approach for Continuous Emotion Recognition in Valence-Arousal Space
Technical Approach for the EMI Challenge in the 8th Affective Behavior Analysis in-the-Wild Competition
CULEMO: Cultural Lenses on Emotion -- Benchmarking LLMs for Cross-Cultural Emotion Understanding
CALLM: Understanding Cancer Survivors' Emotions and Intervention Opportunities via Mobile Diaries and Context-Aware Language Models
Synthetic Data Generation of Body Motion Data by Neural Gas Network for Emotion Recognition
Heterogeneous bimodal attention fusion for speech emotion recognition
Multimodal Emotion Recognition and Sentiment Analysis in Multi-Party Conversation Contexts
Bimodal Connection Attention Fusion for Speech Emotion Recognition
R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning
Personalized Emotion Detection from Floor Vibrations Induced by Footsteps
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations
ECG-EmotionNet: Nested Mixture of Expert (NMoE) Adaptation of ECG-Foundation Model for Driver Emotion Recognition
A novel Fourier Adjacency Transformer for advanced EEG emotion recognition
Steering Language Model to Stable Speech Emotion Recognition via Contextual Perception and Chain of Thought
Teleology-Driven Affective Computing: A Causal Framework for Sustained Well-Being
Latent Distribution Decoupling: A Probabilistic Framework for Uncertainty-Aware Multimodal Emotion Recognition
MSE-Adapter: A Lightweight Plugin Endowing LLMs with the Capability to Perform Multimodal Sentiment Analysis and Emotion Recognition
A Survey of Personalized Large Language Models: Progress and Future Directions
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages
Akan Cinematic Emotions (ACE): A Multimodal Multi-party Dataset for Emotion Recognition in Movie Dialogues
Interpretable Concept-based Deep Learning Framework for Multimodal Human Behavior Modeling
A Novel Dialect-Aware Framework for the Classification of Arabic Dialects and Emotions
A Novel Approach to for Multimodal Emotion Recognition : Multimodal semantic information fusion
Enhancing Higher Education with Generative AI: A Multimodal Approach for Personalised Learning
RAMer: Reconstruction-based Adversarial Model for Multi-party Multi-modal Multi-label Emotion Recognition
Towards Unified Music Emotion Recognition across Dimensional and Categorical Models
EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
Emotion Recognition and Generation: A Comprehensive Review of Face, Speech, and Text Modalities
SigWavNet: Learning Multiresolution Signal Wavelet Network for Speech Emotion Recognition
Milmer: a Framework for Multiple Instance Learning based Multimodal Emotion Recognition
Mini-ResEmoteNet: Leveraging Knowledge Distillation for Human-Centered Design
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