<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="owczarzak-etal-2006-wrapper">
    <titleInfo>
        <title>Wrapper Syntax for Example-based Machine Translation</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Karolina</namePart>
        <namePart type="family">Owczarzak</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Bart</namePart>
        <namePart type="family">Mellebeek</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Declan</namePart>
        <namePart type="family">Groves</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Josef</namePart>
        <namePart type="family">Van Genabith</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Andy</namePart>
        <namePart type="family">Way</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2006-aug 8-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Machine Translation in the Americas</publisher>
            <place>
                <placeTerm type="text">Cambridge, Massachusetts, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>TransBooster is a wrapper technology designed to improve the performance of wide-coverage machine translation systems. Using linguistically motivated syntactic information, it automatically decomposes source language sentences into shorter and syntactically simpler chunks, and recomposes their translation to form target language sentences. This generally improves both the word order and lexical selection of the translation. To date, TransBooster has been successfully applied to rule-based MT, statistical MT, and multi-engine MT. This paper presents the application of TransBooster to Example-Based Machine Translation. In an experiment conducted on test sets extracted from Europarl and the Penn II Treebank we show that our method can raise the BLEU score up to 3.8% relative to the EBMT baseline. We also conduct a manual evaluation, showing that TransBooster-enhanced EBMT produces a better output in terms of fluency than the baseline EBMT in 55% of the cases and in terms of accuracy in 53% of the cases.</abstract>
    <identifier type="citekey">owczarzak-etal-2006-wrapper</identifier>
    <location>
        <url>https://aclanthology.org/2006.amta-papers.17/</url>
    </location>
    <part>
        <date>2006-aug 8-12</date>
        <extent unit="page">
            <start>148</start>
            <end>155</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Wrapper Syntax for Example-based Machine Translation
%A Owczarzak, Karolina
%A Mellebeek, Bart
%A Groves, Declan
%A Van Genabith, Josef
%A Way, Andy
%S Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers
%D 2006
%8 aug 8 12
%I Association for Machine Translation in the Americas
%C Cambridge, Massachusetts, USA
%F owczarzak-etal-2006-wrapper
%X TransBooster is a wrapper technology designed to improve the performance of wide-coverage machine translation systems. Using linguistically motivated syntactic information, it automatically decomposes source language sentences into shorter and syntactically simpler chunks, and recomposes their translation to form target language sentences. This generally improves both the word order and lexical selection of the translation. To date, TransBooster has been successfully applied to rule-based MT, statistical MT, and multi-engine MT. This paper presents the application of TransBooster to Example-Based Machine Translation. In an experiment conducted on test sets extracted from Europarl and the Penn II Treebank we show that our method can raise the BLEU score up to 3.8% relative to the EBMT baseline. We also conduct a manual evaluation, showing that TransBooster-enhanced EBMT produces a better output in terms of fluency than the baseline EBMT in 55% of the cases and in terms of accuracy in 53% of the cases.
%U https://aclanthology.org/2006.amta-papers.17/
%P 148-155

Markdown (Informal)

[Wrapper Syntax for Example-based Machine Translation](https://aclanthology.org/2006.amta-papers.17/) (Owczarzak et al., AMTA 2006)

• Wrapper Syntax for Example-based Machine Translation (Owczarzak et al., AMTA 2006)

ACL

• Karolina Owczarzak, Bart Mellebeek, Declan Groves, Josef Van Genabith, and Andy Way. 2006. Wrapper Syntax for Example-based Machine Translation. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 148–155, Cambridge, Massachusetts, USA. Association for Machine Translation in the Americas.