@inproceedings{gervits-scheutz-2018-pardon,
    title = "Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents",
    author = "Gervits, Felix  and
      Scheutz, Matthias",
    editor = "Komatani, Kazunori  and
      Litman, Diane  and
      Yu, Kai  and
      Papangelis, Alex  and
      Cavedon, Lawrence  and
      Nakano, Mikio",
    booktitle = "Proceedings of the 19th Annual {SIG}dial Meeting on Discourse and Dialogue",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/W18-5011/",
    doi = "10.18653/v1/W18-5011",
    pages = "99--109",
    abstract = "Speech overlap is a common phenomenon in natural conversation and in task-oriented interactions. As human-robot interaction (HRI) becomes more sophisticated, the need to effectively manage turn-taking and resolve overlap becomes more important. In this paper, we introduce a computational model for speech overlap resolution in embodied artificial agents. The model identifies when overlap has occurred and uses timing information, dialogue history, and the agent{'}s goals to generate context-appropriate behavior. We implement this model in a Nao robot using the DIARC cognitive robotic architecture. The model is evaluated on a corpus of task-oriented human dialogue, and we find that the robot can replicate many of the most common overlap resolution behaviors found in the human data."
}