@inproceedings{sjoblom-etal-2021-grammatical,
title = "Grammatical Error Generation Based on Translated Fragments",
author = {Sj{\"o}blom, Eetu and
Creutz, Mathias and
Vahtola, Teemu},
editor = "Dobnik, Simon and
{\O}vrelid, Lilja",
booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)",
month = may # " 31--2 " # jun,
year = "2021",
address = "Reykjavik, Iceland (Online)",
publisher = {Link{\"o}ping University Electronic Press, Sweden},
url = "https://aclanthology.org/2021.nodalida-main.44",
pages = "398--403",
abstract = "We perform neural machine translation of sentence fragments in order to create large amounts of training data for English grammatical error correction. Our method aims at simulating mistakes made by second language learners, and produces a wider range of non-native style language in comparison to a state-of-the-art baseline model. We carry out quantitative and qualitative evaluation. Our method is shown to outperform the baseline on data with a high proportion of errors.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sjoblom-etal-2021-grammatical">
<titleInfo>
<title>Grammatical Error Generation Based on Translated Fragments</title>
</titleInfo>
<name type="personal">
<namePart type="given">Eetu</namePart>
<namePart type="family">Sjöblom</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mathias</namePart>
<namePart type="family">Creutz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Teemu</namePart>
<namePart type="family">Vahtola</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2021-may 31–2 jun</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Simon</namePart>
<namePart type="family">Dobnik</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lilja</namePart>
<namePart type="family">Øvrelid</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Linköping University Electronic Press, Sweden</publisher>
<place>
<placeTerm type="text">Reykjavik, Iceland (Online)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>We perform neural machine translation of sentence fragments in order to create large amounts of training data for English grammatical error correction. Our method aims at simulating mistakes made by second language learners, and produces a wider range of non-native style language in comparison to a state-of-the-art baseline model. We carry out quantitative and qualitative evaluation. Our method is shown to outperform the baseline on data with a high proportion of errors.</abstract>
<identifier type="citekey">sjoblom-etal-2021-grammatical</identifier>
<location>
<url>https://aclanthology.org/2021.nodalida-main.44</url>
</location>
<part>
<date>2021-may 31–2 jun</date>
<extent unit="page">
<start>398</start>
<end>403</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Grammatical Error Generation Based on Translated Fragments
%A Sjöblom, Eetu
%A Creutz, Mathias
%A Vahtola, Teemu
%Y Dobnik, Simon
%Y Øvrelid, Lilja
%S Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)
%D 2021
%8 may 31–2 jun
%I Linköping University Electronic Press, Sweden
%C Reykjavik, Iceland (Online)
%F sjoblom-etal-2021-grammatical
%X We perform neural machine translation of sentence fragments in order to create large amounts of training data for English grammatical error correction. Our method aims at simulating mistakes made by second language learners, and produces a wider range of non-native style language in comparison to a state-of-the-art baseline model. We carry out quantitative and qualitative evaluation. Our method is shown to outperform the baseline on data with a high proportion of errors.
%U https://aclanthology.org/2021.nodalida-main.44
%P 398-403
Markdown (Informal)
[Grammatical Error Generation Based on Translated Fragments](https://aclanthology.org/2021.nodalida-main.44) (Sjöblom et al., NoDaLiDa 2021)
ACL
- Eetu Sjöblom, Mathias Creutz, and Teemu Vahtola. 2021. Grammatical Error Generation Based on Translated Fragments. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), pages 398–403, Reykjavik, Iceland (Online). Linköping University Electronic Press, Sweden.