@inproceedings{zampieri-etal-2017-native,
    title = "Native Language Identification on Text and Speech",
    author = "Zampieri, Marcos  and
      Ciobanu, Alina Maria  and
      Dinu, Liviu P.",
    editor = "Tetreault, Joel  and
      Burstein, Jill  and
      Leacock, Claudia  and
      Yannakoudakis, Helen",
    booktitle = "Proceedings of the 12th Workshop on Innovative Use of {NLP} for Building Educational Applications",
    month = sep,
    year = "2017",
    address = "Copenhagen, Denmark",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/W17-5045/",
    doi = "10.18653/v1/W17-5045",
    pages = "398--404",
    abstract = "This paper presents an ensemble system combining the output of multiple SVM classifiers to native language identification (NLI). The system was submitted to the NLI Shared Task 2017 fusion track which featured students essays and spoken responses in form of audio transcriptions and iVectors by non-native English speakers of eleven native languages. Our system competed in the challenge under the team name ZCD and was based on an ensemble of SVM classifiers trained on character n-grams achieving 83.58{\%} accuracy and ranking 3rd in the shared task."
}