@inproceedings{straka-etal-2021-character,
    title = "Character Transformations for Non-Autoregressive {GEC} Tagging",
    author = "Straka, Milan  and
      N{\'a}plava, Jakub  and
      Strakov{\'a}, Jana",
    editor = "Xu, Wei  and
      Ritter, Alan  and
      Baldwin, Tim  and
      Rahimi, Afshin",
    booktitle = "Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)",
    month = nov,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.wnut-1.46/",
    doi = "10.18653/v1/2021.wnut-1.46",
    pages = "417--422",
    abstract = "We propose a character-based non-autoregressive GEC approach, with automatically generated character transformations. Recently, per-word classification of correction edits has proven an efficient, parallelizable alternative to current encoder-decoder GEC systems. We show that word replacement edits may be suboptimal and lead to explosion of rules for spelling, diacritization and errors in morphologically rich languages, and propose a method for generating character transformations from GEC corpus. Finally, we train character transformation models for Czech, German and Russian, reaching solid results and dramatic speedup compared to autoregressive systems. The source code is released at \url{https://github.com/ufal/wnut2021_character_transformations_gec}."
}