<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="knowles-koehn-2016-neural">
    <titleInfo>
        <title>Neural Interactive Translation Prediction</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Rebecca</namePart>
        <namePart type="family">Knowles</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Philipp</namePart>
        <namePart type="family">Koehn</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-oct 28 - nov 1</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Conferences of the Association for Machine Translation in the Americas: MT Researchers’ Track</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Spence</namePart>
            <namePart type="family">Green</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lane</namePart>
            <namePart type="family">Schwartz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>The Association for Machine Translation in the Americas</publisher>
            <place>
                <placeTerm type="text">Austin, TX, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We present an interactive translation prediction method based on neural machine translation. Even with the same translation quality of the underlying machine translation systems, the neural prediction method yields much higher word prediction accuracy (61.6% vs. 43.3%) than the traditional method based on search graphs, mainly due to better recovery from errors. We also develop efficient means to enable practical deployment.</abstract>
    <identifier type="citekey">knowles-koehn-2016-neural</identifier>
    <location>
        <url>https://aclanthology.org/2016.amta-researchers.9</url>
    </location>
    <part>
        <date>2016-oct 28 - nov 1</date>
        <extent unit="page">
            <start>107</start>
            <end>120</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Neural Interactive Translation Prediction
%A Knowles, Rebecca
%A Koehn, Philipp
%Y Green, Spence
%Y Schwartz, Lane
%S Conferences of the Association for Machine Translation in the Americas: MT Researchers’ Track
%D 2016
%8 oct 28  nov 1
%I The Association for Machine Translation in the Americas
%C Austin, TX, USA
%F knowles-koehn-2016-neural
%X We present an interactive translation prediction method based on neural machine translation. Even with the same translation quality of the underlying machine translation systems, the neural prediction method yields much higher word prediction accuracy (61.6% vs. 43.3%) than the traditional method based on search graphs, mainly due to better recovery from errors. We also develop efficient means to enable practical deployment.
%U https://aclanthology.org/2016.amta-researchers.9
%P 107-120

Markdown (Informal)

[Neural Interactive Translation Prediction](https://aclanthology.org/2016.amta-researchers.9) (Knowles & Koehn, AMTA 2016)

• Neural Interactive Translation Prediction (Knowles & Koehn, AMTA 2016)

ACL

• Rebecca Knowles and Philipp Koehn. 2016. Neural Interactive Translation Prediction. In Conferences of the Association for Machine Translation in the Americas: MT Researchers' Track, pages 107–120, Austin, TX, USA. The Association for Machine Translation in the Americas.