تقرير
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies
| العنوان: | Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies |
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| المؤلفون: | Zhao, Sicheng, Jia, Guoli, Yang, Jufeng, Ding, Guiguang, Keutzer, Kurt |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multimedia |
| الوصف: | Humans are emotional creatures. Multiple modalities are often involved when we express emotions, whether we do so explicitly (e.g., facial expression, speech) or implicitly (e.g., text, image). Enabling machines to have emotional intelligence, i.e., recognizing, interpreting, processing, and simulating emotions, is becoming increasingly important. In this tutorial, we discuss several key aspects of multi-modal emotion recognition (MER). We begin with a brief introduction on widely used emotion representation models and affective modalities. We then summarize existing emotion annotation strategies and corresponding computational tasks, followed by the description of main challenges in MER. Furthermore, we present some representative approaches on representation learning of each affective modality, feature fusion of different affective modalities, classifier optimization for MER, and domain adaptation for MER. Finally, we outline several real-world applications and discuss some future directions. Comment: Accepted by IEEE Signal Processing Magazine (SPM) |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1109/MSP.2021.3106895 |
| URL الوصول: | http://arxiv.org/abs/2108.10152 |
| رقم الأكسشن: | edsarx.2108.10152 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1109/MSP.2021.3106895 |
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