The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

Dialogues with robots frequently exhibit social dialogue acts such as greeting, thanks, and goodbye. This opens the opportunity of using these dialogue acts for dialogue management, in particular for detecting misunderstandings. Our corpus analysis shows that the social dialogue acts have different scopes of their associations with the discourse features within the dialogue: greeting in the user's first turn is associated with such distant, or global, features as the likelihood of having questions answered, persistence, and ending with bye. The user's thanks turn, on the other hand, is strongly associated with the helpfulness of the preceding robot's answer. We therefore interpret the greeting as a component of a user model that can provide information about the user's traits and be associated with discourse features at various stages of the dialogue. We conduct a detailed analysis of the user's thanking behavior and demonstrate that user's thanks can be used in the detection of unhelpful robot's answers. Incorporating the greeting information further improves the detection. We discuss possible applications of this work for human-robot dialogue management.

Keywords

dialogue, politeness, social interaction, human-robot interaction

Notes

Sponsor: Qatar National Research Fund

Associated Center(s) / Consortia: Vision and Autonomous Systems Center, Quality of Life Technology Center, and Center for the Foundations of Robotics

Associated Lab(s) / Group(s): Reliable Autonomous Systems Lab, Planning and Autonomy Lab, Human-Robot Interaction Group

Associated Project(s): Roboceptionist

Number of pages: 6

Text Reference

Maxim Makatchev and Reid Simmons, "Incorporating a User Model to Improve Detection of Unhelpful Robot Answers," International Symposium on Robot and Human Interactive Communication, RO-MAN'2009, September, 2009, pp. 973-978.

BibTeX Reference

@inproceedings{Makatchev_2009_6467,
   author = "Maxim Makatchev and Reid Simmons",
   title = "Incorporating a User Model to Improve Detection of Unhelpful Robot Answers",
   booktitle = "International Symposium on Robot and Human Interactive Communication, RO-MAN'2009",
   pages = "973-978",
   publisher = "IEEE",
   month = "September",
   year = "2009",
}

The Robotics Institute

Menu