<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="stein-etal-2010-cocktail">
    <titleInfo>
        <title>A Cocktail of Deep Syntactic Features for Hierarchical Machine Translation</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Daniel</namePart>
        <namePart type="family">Stein</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Stephan</namePart>
        <namePart type="family">Peitz</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">David</namePart>
        <namePart type="family">Vilar</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Hermann</namePart>
        <namePart type="family">Ney</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2010-oct 31-nov 4</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Machine Translation in the Americas</publisher>
            <place>
                <placeTerm type="text">Denver, Colorado, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>In this work we review and compare three additional syntactic enhancements for the hierarchical phrase-based translation model, which have been presented in the last few years. We compare their performance when applied separately and study whether the combination may yield additional improvements. Our findings show that the models are complementary, and their combination achieve an increase of 1% in BLEU and a reduction of nearly 2% in TER. The models presented in this work are made available as part of the Jane open source machine translation toolkit.</abstract>
    <identifier type="citekey">stein-etal-2010-cocktail</identifier>
    <location>
        <url>https://aclanthology.org/2010.amta-papers.8</url>
    </location>
    <part>
        <date>2010-oct 31-nov 4</date>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T A Cocktail of Deep Syntactic Features for Hierarchical Machine Translation
%A Stein, Daniel
%A Peitz, Stephan
%A Vilar, David
%A Ney, Hermann
%S Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2010
%8 oct 31 nov 4
%I Association for Machine Translation in the Americas
%C Denver, Colorado, USA
%F stein-etal-2010-cocktail
%X In this work we review and compare three additional syntactic enhancements for the hierarchical phrase-based translation model, which have been presented in the last few years. We compare their performance when applied separately and study whether the combination may yield additional improvements. Our findings show that the models are complementary, and their combination achieve an increase of 1% in BLEU and a reduction of nearly 2% in TER. The models presented in this work are made available as part of the Jane open source machine translation toolkit.
%U https://aclanthology.org/2010.amta-papers.8

Markdown (Informal)

[A Cocktail of Deep Syntactic Features for Hierarchical Machine Translation](https://aclanthology.org/2010.amta-papers.8) (Stein et al., AMTA 2010)

• A Cocktail of Deep Syntactic Features for Hierarchical Machine Translation (Stein et al., AMTA 2010)

ACL

• Daniel Stein, Stephan Peitz, David Vilar, and Hermann Ney. 2010. A Cocktail of Deep Syntactic Features for Hierarchical Machine Translation. In Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers, Denver, Colorado, USA. Association for Machine Translation in the Americas.