@inproceedings{keizer-etal-2019-user,
    title = "User Evaluation of a Multi-dimensional Statistical Dialogue System",
    author = "Keizer, Simon  and
      Du{\v{s}}ek, Ond{\v{r}}ej  and
      Liu, Xingkun  and
      Rieser, Verena",
    editor = "Nakamura, Satoshi  and
      Gasic, Milica  and
      Zukerman, Ingrid  and
      Skantze, Gabriel  and
      Nakano, Mikio  and
      Papangelis, Alexandros  and
      Ultes, Stefan  and
      Yoshino, Koichiro",
    booktitle = "Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue",
    month = sep,
    year = "2019",
    address = "Stockholm, Sweden",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/W19-5945/",
    doi = "10.18653/v1/W19-5945",
    pages = "392--398",
    abstract = "We present the first complete spoken dialogue system driven by a multiimensional statistical dialogue manager. This framework has been shown to substantially reduce data needs by leveraging domain-independent dimensions, such as social obligations or feedback, which (as we show) can be transferred between domains. In this paper, we conduct a user study and show that the performance of a multi-dimensional system, which can be adapted from a source domain, is equivalent to that of a one-dimensional baseline, which can only be trained from scratch."
}