@inproceedings{ahmadi-masoud-2020-towards,
    title = "Towards Machine Translation for the {K}urdish Language",
    author = "Ahmadi, Sina  and
      Masoud, Maraim",
    editor = "Karakanta, Alina  and
      Ojha, Atul Kr.  and
      Liu, Chao-Hong  and
      Abbott, Jade  and
      Ortega, John  and
      Washington, Jonathan  and
      Oco, Nathaniel  and
      Lakew, Surafel Melaku  and
      Pirinen, Tommi A  and
      Malykh, Valentin  and
      Logacheva, Varvara  and
      Zhao, Xiaobing",
    booktitle = "Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages",
    month = dec,
    year = "2020",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.loresmt-1.12/",
    doi = "10.18653/v1/2020.loresmt-1.12",
    pages = "87--98",
    abstract = "Machine translation is the task of translating texts from one language to another using computers. It has been one of the major tasks in natural language processing and computational linguistics and has been motivating to facilitate human communication. Kurdish, an Indo-European language, has received little attention in this realm due to the language being less-resourced. Therefore, in this paper, we are addressing the main issues in creating a machine translation system for the Kurdish language, with a focus on the Sorani dialect. We describe the available scarce parallel data suitable for training a neural machine translation model for Sorani Kurdish-English translation. We also discuss some of the major challenges in Kurdish language translation and demonstrate how fundamental text processing tasks, such as tokenization, can improve translation performance."
}