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        <title>Grammatical Error Correction in Low-Resource Scenarios</title>
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            <title>Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)</title>
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        <name type="personal">
            <namePart type="given">Wei</namePart>
            <namePart type="family">Xu</namePart>
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    <abstract>Grammatical error correction in English is a long studied problem with many existing systems and datasets. However, there has been only a limited research on error correction of other languages. In this paper, we present a new dataset AKCES-GEC on grammatical error correction for Czech. We then make experiments on Czech, German and Russian and show that when utilizing synthetic parallel corpus, Transformer neural machine translation model can reach new state-of-the-art results on these datasets. AKCES-GEC is published under CC BY-NC-SA 4.0 license at http://hdl.handle.net/11234/1-3057, and the source code of the GEC model is available at https://github.com/ufal/low-resource-gec-wnut2019.</abstract>
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%0 Conference Proceedings
%T Grammatical Error Correction in Low-Resource Scenarios
%A Náplava, Jakub
%A Straka, Milan
%Y Xu, Wei
%Y Ritter, Alan
%Y Baldwin, Tim
%Y Rahimi, Afshin
%S Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F naplava-straka-2019-grammatical
%X Grammatical error correction in English is a long studied problem with many existing systems and datasets. However, there has been only a limited research on error correction of other languages. In this paper, we present a new dataset AKCES-GEC on grammatical error correction for Czech. We then make experiments on Czech, German and Russian and show that when utilizing synthetic parallel corpus, Transformer neural machine translation model can reach new state-of-the-art results on these datasets. AKCES-GEC is published under CC BY-NC-SA 4.0 license at http://hdl.handle.net/11234/1-3057, and the source code of the GEC model is available at https://github.com/ufal/low-resource-gec-wnut2019.
%R 10.18653/v1/D19-5545
%U https://aclanthology.org/D19-5545
%U https://doi.org/10.18653/v1/D19-5545
%P 346-356

Markdown (Informal)

[Grammatical Error Correction in Low-Resource Scenarios](https://aclanthology.org/D19-5545) (Náplava & Straka, WNUT 2019)

• Grammatical Error Correction in Low-Resource Scenarios (Náplava & Straka, WNUT 2019)

ACL

• Jakub Náplava and Milan Straka. 2019. Grammatical Error Correction in Low-Resource Scenarios. In Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), pages 346–356, Hong Kong, China. Association for Computational Linguistics.