  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.
