Abstract
This paper addresses the question of how and when a robot should interrupt a meeting-style conversation between humans. First, we observed one-to-one human-human conversations. We then employed raters to estimate how easy it was to interrupt each participant in the video. At the same time, we gathered behavioral information about the collocutors (presence of speech, head pose and gaze direction). After establishing that the raters’ ratings were similar, we trained a neural network with the behavioral data as input and the interruptibility measure as output of the system. Once we validated the similarity between the output of our estimator and the actual interruptiblitiy ratings, we proceeded to implement this system on our desktop social robot, CommU. We then used CommU in a human-robot interaction environment, to investigate how the robot should barge-in into a conversation between multiple humans. We compared different approaches to interruption and found that users liked the interruptibility estimation system better than a baseline system which doesn’t pay attention to the state of the speakers. They also preferred the robot to give advance non-verbal notifications of its intention to speak.
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References
Sacks, H., Schegloff, E.A., Jefferson, G.: A simplest systematics for the organization of turn-taking for conversation. Language (Baltim) 50(4), 696 (1974)
Argyle, M., Cook, M.: Gaze and Mutual Gaze. Cambridge University Press, Cambridge (1976)
Schiffrin, D.: Discourse Markers, vol. 107. Cambridge University Press, Cambridge (1987)
Nagao, K., Takeuchi, A.: Social interaction: multimodal social interaction: conversation with social agents, vol. 94. In: AAAI (1994)
Heins, R., Franzke, M., Durian, M., Bayya, A.: Turn-taking as a design principle for barge-in in spoken language systems. Int. J. Speech Technol. 2(2), 155–164 (1997)
Ström, N., Seneff, S.: Intelligent barge-in in conversational systems. In: International Conference on Spoken Language Processing, pp. 1–4 (2000)
Sidner, C.L., Lee, C., Kidd, C.D., Lesh, N., Rich, C.: Explorations in engagement for humans and robots. Artif. Intell. 166(1–2), 140–164 (2005)
Hayashi, K., Kanda, T., Miyashita, T., Ishiguro, H., Hagita, N.: Robot Manzai - robots’ conversation as a passive social medium. In: Proceedings of 2005 5th IEEE-RAS International Conference on Humanoid Robots, vol. 2005, pp. 456–462 (2005)
Iio, T., Yoshikawa, Y., Ishiguro, H.: Starting a conversation by multi-robot cooperative behavior. In: Kheddar, A., et al. (eds.) Social Robotics, vol. 10652. Springer, Cham (2017)
Mutlu, B., Shiwa, T., Kanda, T., Ishiguro, H., Hagita, N.: Footing in human-robot conversations: how robots might shape participant roles using gaze cues. Hum. Factors 2(1), 61–68 (2009)
Matsusaka, Y., Fujie, S., Kobayashi, T.: Modeling of conversational strategy for the robot participating in the group conversation. In: Proceedings of the 7th European Conference on Speech Communication and Technology, pp. 2173–2176 (2001)
Matsusaka, Y., Tojo, T., Kubota, S.: Multi-person conversation via multi-modal interface - a robot who communicate with multi-user. In: Eurospeech, pp. 1723–1726 (1999)
Sasse, A., Johnson, C., et al.: Coordinating the interruption of people in human-computer interaction. In: Human-computer interaction, INTERACT, vol. 99, p. 295 (1999)
Gillie, T., Broadbent, D.: What makes interruptions disruptive? A study of length, similarity, and complexity. Psychol. Res. 50(4), 243–250 (1989)
Stern, H., Pammer, V., Lindstaedt, S.N.: A preliminary study on interruptibility detection based on location and calendar information. In: Proceedings of CoSDEO, vol. 11 (2011)
Mutlu, B., Forlizzi, J.: Robots in organizations: the role of workflow, social, and environmental factors in human-robot interaction. In: 3rd International Conference on Human-Robot Interaction (HRI) (2008)
Rosenthal, S., Veloso, M.: Is someone in this office available to help me? J. Intell. Robot. Syst. 66, 205–221 (2011)
Shi, C., Shiomi, M., Kanda, T., Ishiguro, H., Hagita, N.: Measuring communication participation to initiate conversation in human–robot interaction. Int. J. Soc. Robot. 7(5), 889–910 (2015)
Satake, S., Kanda, T., Glas, D.F., Imai, M., Ishiguro, H., Hagita, N.: How to approach humans?: strategies for social robots to initiate interaction. J. Robot. Soc. Japan 28(3), 109–116 (2010)
Banerjee, S., Chernova, S.: Temporal models for robot classification of human interruptibility. In: Proceedings of the 16th Conference on Autonomous Agents and Multiagent Systems (2017)
Baltrusaitis, T., Robinson, P., Morency, L.P.: 3D constrained local model for rigid and non-rigid facial tracking. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2610–2617 (2012)
Palinko, O., Rea, F., Sandini, G., Sciutti, A.: A robot reading human gaze: why eye tracking is better than head tracking for human-robot collaboration. In: Proceedings of 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Acknowledgements
This research was partially supported by ERATO ISHIGURO Symbiotic Human-Robot Interaction Project and Itoki Corporation. The authors would like to thank Yutaka Nakamura for his help with learning algorithms.
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Palinko, O., Ogawa, K., Yoshikawa, Y., Ishiguro, H. (2018). How Should a Robot Interrupt a Conversation Between Multiple Humans. In: Ge, S., et al. Social Robotics. ICSR 2018. Lecture Notes in Computer Science(), vol 11357. Springer, Cham. https://doi.org/10.1007/978-3-030-05204-1_15
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DOI: https://doi.org/10.1007/978-3-030-05204-1_15
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