<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="tan-2016-faster">
    <titleInfo>
        <title>Faster and Lighter Phrase-based Machine Translation Baseline</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Liling</namePart>
        <namePart type="family">Tan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 3rd Workshop on Asian Translation (WAT2016)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Toshiaki</namePart>
            <namePart type="family">Nakazawa</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Hideya</namePart>
            <namePart type="family">Mino</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Chenchen</namePart>
            <namePart type="family">Ding</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Isao</namePart>
            <namePart type="family">Goto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Graham</namePart>
            <namePart type="family">Neubig</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sadao</namePart>
            <namePart type="family">Kurohashi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ir.</namePart>
            <namePart type="given">Hammam</namePart>
            <namePart type="family">Riza</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Pushpak</namePart>
            <namePart type="family">Bhattacharyya</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>The COLING 2016 Organizing Committee</publisher>
            <place>
                <placeTerm type="text">Osaka, Japan</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper describes the SENSE machine translation system participation in the Third Workshop for Asian Translation (WAT2016). We share our best practices to build a fast and light phrase-based machine translation (PBMT) models that have comparable results to the baseline systems provided by the organizers. As Neural Machine Translation (NMT) overtakes PBMT as the state-of-the-art, deep learning and new MT practitioners might not be familiar with the PBMT paradigm and we hope that this paper will help them build a PBMT baseline system quickly and easily.</abstract>
    <identifier type="citekey">tan-2016-faster</identifier>
    <location>
        <url>https://aclanthology.org/W16-4618/</url>
    </location>
    <part>
        <date>2016-12</date>
        <extent unit="page">
            <start>184</start>
            <end>193</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Faster and Lighter Phrase-based Machine Translation Baseline
%A Tan, Liling
%Y Nakazawa, Toshiaki
%Y Mino, Hideya
%Y Ding, Chenchen
%Y Goto, Isao
%Y Neubig, Graham
%Y Kurohashi, Sadao
%Y Riza, Ir. Hammam
%Y Bhattacharyya, Pushpak
%S Proceedings of the 3rd Workshop on Asian Translation (WAT2016)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F tan-2016-faster
%X This paper describes the SENSE machine translation system participation in the Third Workshop for Asian Translation (WAT2016). We share our best practices to build a fast and light phrase-based machine translation (PBMT) models that have comparable results to the baseline systems provided by the organizers. As Neural Machine Translation (NMT) overtakes PBMT as the state-of-the-art, deep learning and new MT practitioners might not be familiar with the PBMT paradigm and we hope that this paper will help them build a PBMT baseline system quickly and easily.
%U https://aclanthology.org/W16-4618/
%P 184-193

Markdown (Informal)

[Faster and Lighter Phrase-based Machine Translation Baseline](https://aclanthology.org/W16-4618/) (Tan, WAT 2016)

• Faster and Lighter Phrase-based Machine Translation Baseline (Tan, WAT 2016)

ACL

• Liling Tan. 2016. Faster and Lighter Phrase-based Machine Translation Baseline. In Proceedings of the 3rd Workshop on Asian Translation (WAT2016), pages 184–193, Osaka, Japan. The COLING 2016 Organizing Committee.