@inproceedings{xu-etal-2019-systran,
    title = "{SYSTRAN} @ {WAT} 2019: {R}ussian-{J}apanese News Commentary task",
    author = "Xu, Jitao  and
      Nguyen, TuAnh  and
      Pham, MinhQuang  and
      Crego, Josep  and
      Senellart, Jean",
    editor = "Nakazawa, Toshiaki  and
      Ding, Chenchen  and
      Dabre, Raj  and
      Kunchukuttan, Anoop  and
      Doi, Nobushige  and
      Oda, Yusuke  and
      Bojar, Ond{\v{r}}ej  and
      Parida, Shantipriya  and
      Goto, Isao  and
      Mino, Hidaya",
    booktitle = "Proceedings of the 6th Workshop on Asian Translation",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/D19-5225/",
    doi = "10.18653/v1/D19-5225",
    pages = "189--194",
    abstract = "This paper describes Systran`s submissions to WAT 2019 Russian-Japanese News Commentary task. A challenging translation task due to the extremely low resources available and the distance of the language pair. We have used the neural Transformer architecture learned over the provided resources and we carried out synthetic data generation experiments which aim at alleviating the data scarcity problem. Results indicate the suitability of the data augmentation experiments, enabling our systems to rank first according to automatic evaluations."
}