@inproceedings{foster-etal-2002-text,
title = "Text prediction with fuzzy alignment",
author = "Foster, George and
Langlais, Philippe and
Lapalme, Guy",
editor = "Richardson, Stephen D.",
booktitle = "Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers",
month = oct # " 8-12",
year = "2002",
address = "Tiburon, USA",
publisher = "Springer",
url = "https://link.springer.com/chapter/10.1007/3-540-45820-4_5",
pages = "44--53",
abstract = "Text prediction is a form of interactive machine translation that is well suited to skilled translators. In recent work it has been shown that simple statistical translation models can be applied within a usermodeling framework to improve translator productivity by over 10{\%} in simulated results. For the sake of efficiency in making real-time predictions, these models ignore the alignment relation between source and target texts. In this paper we introduce a new model that captures fuzzy alignments in a very simple way, and show that it gives modest improvements in predictive performance without significantly increasing the time required to generate predictions.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="foster-etal-2002-text">
<titleInfo>
<title>Text prediction with fuzzy alignment</title>
</titleInfo>
<name type="personal">
<namePart type="given">George</namePart>
<namePart type="family">Foster</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Philippe</namePart>
<namePart type="family">Langlais</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Guy</namePart>
<namePart type="family">Lapalme</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2002-oct 8-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers</title>
</titleInfo>
<name type="personal">
<namePart type="given">Stephen</namePart>
<namePart type="given">D</namePart>
<namePart type="family">Richardson</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Springer</publisher>
<place>
<placeTerm type="text">Tiburon, USA</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Text prediction is a form of interactive machine translation that is well suited to skilled translators. In recent work it has been shown that simple statistical translation models can be applied within a usermodeling framework to improve translator productivity by over 10% in simulated results. For the sake of efficiency in making real-time predictions, these models ignore the alignment relation between source and target texts. In this paper we introduce a new model that captures fuzzy alignments in a very simple way, and show that it gives modest improvements in predictive performance without significantly increasing the time required to generate predictions.</abstract>
<identifier type="citekey">foster-etal-2002-text</identifier>
<location>
<url>https://link.springer.com/chapter/10.1007/3-540-45820-4_5</url>
</location>
<part>
<date>2002-oct 8-12</date>
<extent unit="page">
<start>44</start>
<end>53</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Text prediction with fuzzy alignment
%A Foster, George
%A Langlais, Philippe
%A Lapalme, Guy
%Y Richardson, Stephen D.
%S Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers
%D 2002
%8 oct 8 12
%I Springer
%C Tiburon, USA
%F foster-etal-2002-text
%X Text prediction is a form of interactive machine translation that is well suited to skilled translators. In recent work it has been shown that simple statistical translation models can be applied within a usermodeling framework to improve translator productivity by over 10% in simulated results. For the sake of efficiency in making real-time predictions, these models ignore the alignment relation between source and target texts. In this paper we introduce a new model that captures fuzzy alignments in a very simple way, and show that it gives modest improvements in predictive performance without significantly increasing the time required to generate predictions.
%U https://link.springer.com/chapter/10.1007/3-540-45820-4_5
%P 44-53
Markdown (Informal)
[Text prediction with fuzzy alignment](https://link.springer.com/chapter/10.1007/3-540-45820-4_5) (Foster et al., AMTA 2002)
ACL
- George Foster, Philippe Langlais, and Guy Lapalme. 2002. Text prediction with fuzzy alignment. In Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 44–53, Tiburon, USA. Springer.