@inproceedings{bestgen-2021-using,
    title = "Using {C}oll{G}ram to Compare Formulaic Language in Human and Machine Translation",
    author = "Bestgen, Yves",
    editor = "Mitkov, Ruslan  and
      Sosoni, Vilelmini  and
      Gigu{\`e}re, Julie Christine  and
      Murgolo, Elena  and
      Deysel, Elizabeth",
    booktitle = "Proceedings of the Translation and Interpreting Technology Online Conference",
    month = jul,
    year = "2021",
    address = "Held Online",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.triton-1.20/",
    pages = "174--180",
    abstract = "A comparison of formulaic sequences in human and neural machine translation of quality newspaper articles shows that neural machine translations contain less lower-frequency, but strongly-associated formulaic sequences (FSs), and more high-frequency FSs. These observations can be related to the differences between second language learners of various levels and between translated and untranslated texts. The comparison between the neural machine translation systems indicates that some systems produce more FSs of both types than other systems."
}