@inproceedings{jauhiainen-etal-2018-heli-based,
    title = "{H}e{LI}-based Experiments in {S}wiss {G}erman Dialect Identification",
    author = "Jauhiainen, Tommi  and
      Jauhiainen, Heidi  and
      Lind{\'e}n, Krister",
    editor = {Zampieri, Marcos  and
      Nakov, Preslav  and
      Ljube{\v{s}}i{\'c}, Nikola  and
      Tiedemann, J{\"o}rg  and
      Malmasi, Shervin  and
      Ali, Ahmed},
    booktitle = "Proceedings of the Fifth Workshop on {NLP} for Similar Languages, Varieties and Dialects ({V}ar{D}ial 2018)",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/W18-3929/",
    pages = "254--262",
    abstract = "In this paper we present the experiments and results by the SUKI team in the German Dialect Identification shared task of the VarDial 2018 Evaluation Campaign. Our submission using HeLI with adaptive language models obtained the best results in the shared task with a macro F1-score of 0.686, which is clearly higher than the other submitted results. Without some form of unsupervised adaptation on the test set, it might not be possible to reach as high an F1-score with the level of domain difference between the datasets of the shared task. We describe the methods used in detail, as well as some additional experiments carried out during the shared task."
}