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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
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Can Emotion Fool Anti-spoofing?
Learning Annotation Consensus for Continuous Emotion Recognition
EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary Classification
Knowledge-Aligned Counterfactual-Enhancement Diffusion Perception for Unsupervised Cross-Domain Visual Emotion Recognition
ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs
Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking Model
EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition
Inceptive Transformers: Enhancing Contextual Representations through Multi-Scale Feature Learning Across Domains and Languages
CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training
Audio-to-Audio Emotion Conversion With Pitch And Duration Style Transfer
Contrastive Distillation of Emotion Knowledge from LLMs for Zero-Shot Emotion Recognition
ABHINAYA -- A System for Speech Emotion Recognition In Naturalistic Conditions Challenge
Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning
The Pursuit of Empathy: Evaluating Small Language Models for PTSD Dialogue Support
The Super Emotion Dataset
MIKU-PAL: An Automated and Standardized Multi-Modal Method for Speech Paralinguistic and Affect Labeling
Multimodal Mixture of Low-Rank Experts for Sentiment Analysis and Emotion Recognition
Mitigating Subgroup Disparities in Multi-Label Speech Emotion Recognition: A Pseudo-Labeling and Unsupervised Learning Approach
JNLP at SemEval-2025 Task 11: Cross-Lingual Multi-Label Emotion Detection Using Generative Models
FEALLM: Advancing Facial Emotion Analysis in Multimodal Large Language Models with Emotional Synergy and Reasoning
Emotion Recognition for Low-Resource Turkish: Fine-Tuning BERTurk on TREMO and Testing on Xenophobic Political Discourse
CAMEO: Collection of Multilingual Emotional Speech Corpora
Music Interpretation and Emotion Perception: A Computational and Neurophysiological Investigation
GlobalMood: A cross-cultural benchmark for music emotion recognition
Emotion Knowledge Enhancement for Vision Large Language Models: A Self-Verification Approach for High-Quality Emotion Instruction Data Generation
Interpretable Multi-Task PINN for Emotion Recognition and EDA Prediction
Evaluation in EEG Emotion Recognition: State-of-the-Art Review and Unified Framework
Robust Emotion Recognition via Bi-Level Self-Supervised Continual Learning
Empirical Analysis of Asynchronous Federated Learning on Heterogeneous Devices: Efficiency, Fairness, and Privacy Trade-offs
TACFN: Transformer-based Adaptive Cross-modal Fusion Network for Multimodal Emotion Recognition
Emotion-Qwen: Training Hybrid Experts for Unified Emotion and General Vision-Language Understanding
Artificial Behavior Intelligence: Technology, Challenges, and Future Directions
VAEmo: Efficient Representation Learning for Visual-Audio Emotion with Knowledge Injection
Emotions in the Loop: A Survey of Affective Computing for Emotional Support
BERSting at the Screams: A Benchmark for Distanced, Emotional and Shouted Speech Recognition
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