@inproceedings{arthur-etal-2021-learning,
    title = "Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning",
    author = "Arthur, Philip  and
      Cohn, Trevor  and
      Haffari, Gholamreza",
    editor = "Merlo, Paola  and
      Tiedemann, Jorg  and
      Tsarfaty, Reut",
    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.eacl-main.233/",
    doi = "10.18653/v1/2021.eacl-main.233",
    pages = "2709--2719",
    abstract = "We present a novel approach to efficiently learn a simultaneous translation model with coupled programmer-interpreter policies. First, we present an algorithmic oracle to produce oracle READ/WRITE actions for training bilingual sentence-pairs using the notion of word alignments. This oracle actions are designed to capture enough information from the partial input before writing the output. Next, we perform a coupled scheduled sampling to effectively mitigate the exposure bias when learning both policies jointly with imitation learning. Experiments on six language-pairs show our method outperforms strong baselines in terms of translation quality quality while keeping the delay low."
}