@inproceedings{scherrer-etal-2020-university,
    title = "The {U}niversity of {H}elsinki and Aalto University submissions to the {WMT} 2020 news and low-resource translation tasks",
    author = {Scherrer, Yves  and
      Gr{\"o}nroos, Stig-Arne  and
      Virpioja, Sami},
    editor = {Barrault, Lo{\"i}c  and
      Bojar, Ond{\v{r}}ej  and
      Bougares, Fethi  and
      Chatterjee, Rajen  and
      Costa-juss{\`a}, Marta R.  and
      Federmann, Christian  and
      Fishel, Mark  and
      Fraser, Alexander  and
      Graham, Yvette  and
      Guzman, Paco  and
      Haddow, Barry  and
      Huck, Matthias  and
      Yepes, Antonio Jimeno  and
      Koehn, Philipp  and
      Martins, Andr{\'e}  and
      Morishita, Makoto  and
      Monz, Christof  and
      Nagata, Masaaki  and
      Nakazawa, Toshiaki  and
      Negri, Matteo},
    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Ingest-2025-COMPUTEL/2020.wmt-1.134/",
    pages = "1129--1138",
    abstract = "This paper describes the joint participation of University of Helsinki and Aalto University to two shared tasks of WMT 2020: the news translation between Inuktitut and English and the low-resource translation between German and Upper Sorbian. For both tasks, our efforts concentrate on efficient use of monolingual and related bilingual corpora with scheduled multi-task learning as well as an optimized subword segmentation with sampling. Our submission obtained the highest score for Upper Sorbian -{\ensuremath{>}} German and was ranked second for German -{\ensuremath{>}} Upper Sorbian according to BLEU scores. For English{--}Inuktitut, we reached ranks 8 and 10 out of 11 according to BLEU scores."
}