论文标题
一项关于基于生理信号的情绪识别的调查
A Survey on Physiological Signal Based Emotion Recognition
论文作者
论文摘要
生理信号是情绪识别的最可靠的信号形式，因为它们不能由主题故意控制。现有的关于基于生理信号的情绪识别的评论论文仅对情绪识别工作流程的常规步骤（例如预处理，特征提取和分类）。尽管这些是重要的步骤，但任何信号处理应用都需要这样的步骤。情感认可带来了自己的一系列挑战，这些挑战对于解决强大的系统非常重要。因此，为了弥合现有文献中的差距，在本文中，我们回顾了受试者间数据差异对情绪识别的影响，情感识别的重要数据注释技术及其比较，对每种生理信号的数据预处理技术，数据启用技术的数据启动技术，以改善情感识别模型和不同多种模构技术的普遍化。最后，我们讨论了该领域的主要挑战和未来方向。
Physiological Signals are the most reliable form of signals for emotion recognition, as they cannot be controlled deliberately by the subject. Existing review papers on emotion recognition based on physiological signals surveyed only the regular steps involved in the workflow of emotion recognition such as preprocessing, feature extraction, and classification. While these are important steps, such steps are required for any signal processing application. Emotion recognition poses its own set of challenges that are very important to address for a robust system. Thus, to bridge the gap in the existing literature, in this paper, we review the effect of inter-subject data variance on emotion recognition, important data annotation techniques for emotion recognition and their comparison, data preprocessing techniques for each physiological signal, data splitting techniques for improving the generalization of emotion recognition models and different multimodal fusion techniques and their comparison. Finally we discuss key challenges and future directions in this field.
