@inproceedings{yadav-shrivastava-2021-a3,
    title = "A3-108 Machine Translation System for {L}o{R}es{MT} Shared Task @{MT} Summit 2021 Conference",
    author = "Yadav, Saumitra  and
      Shrivastava, Manish",
    editor = "Ortega, John  and
      Ojha, Atul Kr.  and
      Kann, Katharina  and
      Liu, Chao-Hong",
    booktitle = "Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)",
    month = aug,
    year = "2021",
    address = "Virtual",
    publisher = "Association for Machine Translation in the Americas",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2021.mtsummit-loresmt.12/",
    pages = "124--128",
    abstract = "In this paper, we describe our submissions for LoResMT Shared Task @MT Summit 2021 Conference. We built statistical translation systems in each direction for English {\ensuremath{\Leftarrow}}{\ensuremath{\Rightarrow}} Marathi language pair. This paper outlines initial baseline experiments with various tokenization schemes to train models. Using optimal tokenization scheme we create synthetic data and further train augmented dataset to create more statistical models. Also, we reorder English to match Marathi syntax to further train another set of baseline and data augmented models using various tokenization schemes. We report configuration of the submitted systems and results produced by them."
}