Effects of incomplete utterance on conversational engagement in a multi-party conversation

How can we make it possible for humans to participate in the robot’s speech to aim for a co-constructed conversation? In this paper, we investigated the effects and factors of dialogue design, focusing on incompleteness. We examined the people’s attitudes toward participation in multi-party conversations using human-robot assisted story-telling interactions. The results showed that the utterance strategy of lacking words reduced the passive participation attitude when the talker robot speak to humans directly. If we want to increase people’s participation attitude in a conversation, avoiding conveying much information and using incompleteness is an effective way to do so. However, the results also confirmed that the incomplete utterance was not satisfied to improve people’s co-telling attitude yet. The robots in this study were unable to accept the variety of ways in which people speak. To achieve the co-constructed conversation, discussed how robots could install a variety of actions based on other multi-party conversation studies. Therefore, we also investigated the limitation of multi-party participation and the characteristics of human speeches. For people and systems to have a co-constructed conversation rather than as information transfer, we believe that the design of dialogue needs to change. For this reason, we reported one of the effects of incompleteness conversation design here. © 2021, Japanese Society for Artificial Intelligence. All rights reserved.