@inproceedings{dwiastuti-2019-english,
    title = "{E}nglish-{I}ndonesian Neural Machine Translation for Spoken Language Domains",
    author = "Dwiastuti, Meisyarah",
    editor = "Alva-Manchego, Fernando  and
      Choi, Eunsol  and
      Khashabi, Daniel",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/P19-2043/",
    doi = "10.18653/v1/P19-2043",
    pages = "309--314",
    abstract = "In this work, we conduct a study on Neural Machine Translation (NMT) for English-Indonesian (EN-ID) and Indonesian-English (ID-EN). We focus on spoken language domains, namely colloquial and speech languages. We build NMT systems using the Transformer model for both translation directions and implement domain adaptation, in which we train our pre-trained NMT systems on speech language (in-domain) data. Moreover, we conduct an evaluation on how the domain-adaptation method in our EN-ID system can result in more formal translation outputs."
}