@inproceedings{ma-mckeown-2012-phrase,
title = "Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding",
author = "Ma, Wei-Yun and
McKeown, Kathleen",
booktitle = "Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers",
month = oct # " 28-" # nov # " 1",
year = "2012",
address = "San Diego, California, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2012.amta-papers.11/",
abstract = "In this paper, we propose a novel lattice-based MT combination methodology that we call Target-to-Target Decoding (TTD). The combination process is carried out as a {\textquotedblleft}translation{\textquotedblright} from backbone to the combination result. This perspective suggests the use of existing phrase-based MT techniques in the combination framework. We show how phrase extraction rules and confidence estimations inspired from machine translation improve results. We also propose system-specific LMs for estimating N-gram consensus. Our results show that our approach yields a strong improvement over the best single MT system and competes with other state-of-the-art combination systems."
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ma-mckeown-2012-phrase">
<titleInfo>
<title>Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding</title>
</titleInfo>
<name type="personal">
<namePart type="given">Wei-Yun</namePart>
<namePart type="family">Ma</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kathleen</namePart>
<namePart type="family">McKeown</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2012-oct 28-nov 1</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 10th 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">San Diego, California, USA</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>In this paper, we propose a novel lattice-based MT combination methodology that we call Target-to-Target Decoding (TTD). The combination process is carried out as a “translation” from backbone to the combination result. This perspective suggests the use of existing phrase-based MT techniques in the combination framework. We show how phrase extraction rules and confidence estimations inspired from machine translation improve results. We also propose system-specific LMs for estimating N-gram consensus. Our results show that our approach yields a strong improvement over the best single MT system and competes with other state-of-the-art combination systems.</abstract>
<identifier type="citekey">ma-mckeown-2012-phrase</identifier>
<location>
<url>https://aclanthology.org/2012.amta-papers.11/</url>
</location>
<part>
<date>2012-oct 28-nov 1</date>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding
%A Ma, Wei-Yun
%A McKeown, Kathleen
%S Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2012
%8 oct 28 nov 1
%I Association for Machine Translation in the Americas
%C San Diego, California, USA
%F ma-mckeown-2012-phrase
%X In this paper, we propose a novel lattice-based MT combination methodology that we call Target-to-Target Decoding (TTD). The combination process is carried out as a “translation” from backbone to the combination result. This perspective suggests the use of existing phrase-based MT techniques in the combination framework. We show how phrase extraction rules and confidence estimations inspired from machine translation improve results. We also propose system-specific LMs for estimating N-gram consensus. Our results show that our approach yields a strong improvement over the best single MT system and competes with other state-of-the-art combination systems.
%U https://aclanthology.org/2012.amta-papers.11/
Markdown (Informal)
[Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding](https://aclanthology.org/2012.amta-papers.11/) (Ma & McKeown, AMTA 2012)
ACL