@inproceedings{khayrallah-koehn-2018-impact,
    title = "On the Impact of Various Types of Noise on Neural Machine Translation",
    author = "Khayrallah, Huda  and
      Koehn, Philipp",
    editor = "Birch, Alexandra  and
      Finch, Andrew  and
      Luong, Thang  and
      Neubig, Graham  and
      Oda, Yusuke",
    booktitle = "Proceedings of the 2nd Workshop on Neural Machine Translation and Generation",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/W18-2709/",
    doi = "10.18653/v1/W18-2709",
    pages = "74--83",
    abstract = "We examine how various types of noise in the parallel training data impact the quality of neural machine translation systems. We create five types of artificial noise and analyze how they degrade performance in neural and statistical machine translation. We find that neural models are generally more harmed by noise than statistical models. For one especially egregious type of noise they learn to just copy the input sentence."
}