Diverse disciplines are interested in how the coordination of interacting agents' movements, emotions, and physiology over time impacts social behavior. Here, we describe a new multivariate procedure for automating the investigation of this kind of behaviorally-relevant "interactional synchrony", and introduce a novel interactional synchrony measure based on features of dynamic time warping (DTW) paths. We demonstrate that our DTW path-based measure of interactional synchrony between facial action units of two people interacting freely in a natural social interaction can be used to predict how much trust they will display in a subsequent Trust Game. We also show that our approach outperforms univariate head movement models, models that consider participants' facial action units independently, and models that use previously proposed synchrony or similarity measures. The insights of this work can be applied to any research question that aims to quantify the temporal coordination of multiple signals over time, but has immediate applications in psychology, medicine, and robotics.
翻译:不同学科对互动代理人运动、情感和生理方面的协调如何影响社会行为感兴趣。 在这里, 我们描述一种新的多变程序, 用于自动调查这种与行为相关的“ 互动同步”, 并引入基于动态时间扭曲路径特征的新型互动同步度量。 我们证明, 我们的DTW基于路径的对两个人在自然社会互动中自由互动的面部动作单位之间互动同步度量, 可以用来预测他们在随后的“ 信任游戏” 中将展示多少信任度。 我们还展示了我们的方法超越了对参与者面部动作单元进行独立考虑的模式, 以及使用先前提出的同步或类似测量模型。 这项工作的洞察力可以应用于任何旨在量化多个信号在时间上的协调性的研究问题, 但可以在心理学、 医学 和机器人 中直接应用 。