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    <titleInfo>
        <title>The CUED’s Grammatical Error Correction Systems for BEA-2019</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Felix</namePart>
        <namePart type="family">Stahlberg</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Bill</namePart>
        <namePart type="family">Byrne</namePart>
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        <titleInfo>
            <title>Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Helen</namePart>
            <namePart type="family">Yannakoudakis</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Kochmar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Claudia</namePart>
            <namePart type="family">Leacock</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        </name>
        <name type="personal">
            <namePart type="given">Nitin</namePart>
            <namePart type="family">Madnani</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ildikó</namePart>
            <namePart type="family">Pilán</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        </name>
        <name type="personal">
            <namePart type="given">Torsten</namePart>
            <namePart type="family">Zesch</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <publisher>Association for Computational Linguistics</publisher>
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                <placeTerm type="text">Florence, Italy</placeTerm>
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    <abstract>We describe two entries from the Cambridge University Engineering Department to the BEA 2019 Shared Task on grammatical error correction. Our submission to the low-resource track is based on prior work on using finite state transducers together with strong neural language models. Our system for the restricted track is a purely neural system consisting of neural language models and neural machine translation models trained with back-translation and a combination of checkpoint averaging and fine-tuning – without the help of any additional tools like spell checkers. The latter system has been used inside a separate system combination entry in cooperation with the Cambridge University Computer Lab.</abstract>
    <identifier type="citekey">stahlberg-byrne-2019-cueds</identifier>
    <identifier type="doi">10.18653/v1/W19-4417</identifier>
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        <url>https://aclanthology.org/W19-4417/</url>
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    <part>
        <date>2019-08</date>
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            <start>168</start>
            <end>175</end>
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%0 Conference Proceedings
%T The CUED’s Grammatical Error Correction Systems for BEA-2019
%A Stahlberg, Felix
%A Byrne, Bill
%Y Yannakoudakis, Helen
%Y Kochmar, Ekaterina
%Y Leacock, Claudia
%Y Madnani, Nitin
%Y Pilán, Ildikó
%Y Zesch, Torsten
%S Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F stahlberg-byrne-2019-cueds
%X We describe two entries from the Cambridge University Engineering Department to the BEA 2019 Shared Task on grammatical error correction. Our submission to the low-resource track is based on prior work on using finite state transducers together with strong neural language models. Our system for the restricted track is a purely neural system consisting of neural language models and neural machine translation models trained with back-translation and a combination of checkpoint averaging and fine-tuning – without the help of any additional tools like spell checkers. The latter system has been used inside a separate system combination entry in cooperation with the Cambridge University Computer Lab.
%R 10.18653/v1/W19-4417
%U https://aclanthology.org/W19-4417/
%U https://doi.org/10.18653/v1/W19-4417
%P 168-175

Markdown (Informal)

[The CUED’s Grammatical Error Correction Systems for BEA-2019](https://aclanthology.org/W19-4417/) (Stahlberg & Byrne, BEA 2019)

• The CUED’s Grammatical Error Correction Systems for BEA-2019 (Stahlberg & Byrne, BEA 2019)

ACL

• Felix Stahlberg and Bill Byrne. 2019. The CUED’s Grammatical Error Correction Systems for BEA-2019. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 168–175, Florence, Italy. Association for Computational Linguistics.