@inproceedings{vanmassenhove-hardmeier-2018-europarl,
    title = "{E}uroparl Datasets with Demographic Speaker Information",
    author = "Vanmassenhove, Eva  and
      Hardmeier, Christian",
    editor = "P{\'e}rez-Ortiz, Juan Antonio  and
      S{\'a}nchez-Mart{\'i}nez, Felipe  and
      Espl{\`a}-Gomis, Miquel  and
      Popovi{\'c}, Maja  and
      Rico, Celia  and
      Martins, Andr{\'e}  and
      Van den Bogaert, Joachim  and
      Forcada, Mikel L.",
    booktitle = "Proceedings of the 21st Annual Conference of the European Association for Machine Translation",
    month = may,
    year = "2018",
    address = "Alicante, Spain",
    url = "https://preview.aclanthology.org/fix-sig-urls/2018.eamt-main.59/",
    pages = "391",
    abstract = "Research on speaker-adapted neural machine translation (NMT) is scarce. One of the main challenges for more personalized MT systems is finding large enough annotated parallel datasets with speaker information. Rabinovich et al. (2017) published an annotated parallel dataset for EN{--}FR and EN{--}DE, however, for many other language pairs no sufficiently large annotated datasets are available."
}