@article{komatani-etal-2017-user,
    title = "User-Adaptive A Posteriori Restoration for Incorrectly Segmented Utterances in Spoken Dialogue Systems",
    author = "Komatani, Kazunori  and
      Hotta, Naoki  and
      Sato, Satoshi  and
      Nakano, Mikio",
    editor = "Stent, Amanda  and
      Taboada, Maite  and
      Fern{\'a}ndez, Raquel  and
      Traum, David  and
      Poesio, Massimo  and
      Eugenio, Barbara Di  and
      Stede, Manfred",
    journal = "Dialogue {\&} Discourse",
    volume = "8",
    year = "2017",
    url = "https://preview.aclanthology.org/ingest-dnd/2017.dnd-8.2/",
    doi = "10.5087/dad.2017.209",
    pages = "206--224",
    abstract = "Ideally, the users of spoken dialogue systems should be able to speak at their own tempo. Thus, the systems needs to interpret utterances from various users correctly, even when the utterances contain pauses. In response to this issue, we propose an approach based on a posteriori restoration for incorrectly segmented utterances. A crucial part of this approach is to determine whether restoration is required. We use a classification-based approach, adapted to each user. We focus on each user{'}s dialogue tempo, which can be obtained during the dialogue, and determine the correlation between each user{'}s tempo and the appropriate thresholds for classification. A linear regression function used to convert the tempos into thresholds is also derived. Experimental results show that the proposed user adaptation approach applied to two restoration classification methods, thresholding and decision trees, improves classification accuracies by 3.0{\%} and 7.4{\%}, respectively, in cross validation."
}