论文标题

与社交机器人互动的通行证互动的估计框架

An Estimation Framework for Passerby Engagement Interacting with Social Robots

论文作者

Sakaguchi, Taichi, Okafuji, Yuki, Matsumura, Kohei, Baba, Jun, Nakanishi, Junya

论文摘要

预计社会机器人将是一种人类劳动支持技术,其中一种应用是公共场所中的广告媒介。当社交机器人提供信息(例如推荐商店)时,需要根据用户状态进行自适应沟通。用户参与也被定义为机器人的兴趣水平,可能在自适应沟通中起重要作用。因此,在本文中,我们提出了一个新的框架来估计用户参与度。所提出的方法着重于四个未解决的开放问题:多方互动,国家参与的变化过程,注释参与度的难度以及现实世界中的互动数据集。使用相互作用持续时间评估了提出的估计参与方法的准确性。结果表明,可以通过考虑其他人的行为的影响来准确估算相互作用持续时间。这也意味着所提出的模型可以准确估计与机器人相互作用期间的参与度。

Social robots are expected to be a human labor support technology, and one application of them is an advertising medium in public spaces. When social robots provide information, such as recommended shops, adaptive communication according to the user's state is desired. User engagement, which is also defined as the level of interest in the robot, is likely to play an important role in adaptive communication. Therefore, in this paper, we propose a new framework to estimate user engagement. The proposed method focuses on four unsolved open problems: multi-party interactions, process of state change in engagement, difficulty in annotating engagement, and interaction dataset in the real world. The accuracy of the proposed method for estimating engagement was evaluated using interaction duration. The results show that the interaction duration can be accurately estimated by considering the influence of the behaviors of other people; this also implies that the proposed model accurately estimates the level of engagement during interaction with the robot.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源