@inproceedings{vogel-2005-pesa,
title = "{PESA}: Phrase Pair Extraction as Sentence Splitting",
author = "Vogel, Stephan",
booktitle = "Proceedings of Machine Translation Summit X: Papers",
month = sep # " 13-15",
year = "2005",
address = "Phuket, Thailand",
url = "https://aclanthology.org/2005.mtsummit-papers.33",
pages = "251--258",
abstract = "Most statistical machine translation systems use phrase-to-phrase translations to capture local context information, leading to better lexical choice and more reliable local reordering. The quality of the phrase alignment is crucial to the quality of the resulting translations. Here, we propose a new phrase alignment method, not based on the Viterbi path of word alignment models. Phrase alignment is viewed as a sentence splitting task. For a given spitting of the source sentence (source phrase, left segment, right segment) find a splitting for the target sentence, which optimizes the overall sentence alignment probability. Experiments on different translation tasks show that this phrase alignment method leads to highly competitive translation results.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="vogel-2005-pesa">
<titleInfo>
<title>PESA: Phrase Pair Extraction as Sentence Splitting</title>
</titleInfo>
<name type="personal">
<namePart type="given">Stephan</namePart>
<namePart type="family">Vogel</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2005-sep 13-15</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of Machine Translation Summit X: Papers</title>
</titleInfo>
<originInfo>
<place>
<placeTerm type="text">Phuket, Thailand</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Most statistical machine translation systems use phrase-to-phrase translations to capture local context information, leading to better lexical choice and more reliable local reordering. The quality of the phrase alignment is crucial to the quality of the resulting translations. Here, we propose a new phrase alignment method, not based on the Viterbi path of word alignment models. Phrase alignment is viewed as a sentence splitting task. For a given spitting of the source sentence (source phrase, left segment, right segment) find a splitting for the target sentence, which optimizes the overall sentence alignment probability. Experiments on different translation tasks show that this phrase alignment method leads to highly competitive translation results.</abstract>
<identifier type="citekey">vogel-2005-pesa</identifier>
<location>
<url>https://aclanthology.org/2005.mtsummit-papers.33</url>
</location>
<part>
<date>2005-sep 13-15</date>
<extent unit="page">
<start>251</start>
<end>258</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T PESA: Phrase Pair Extraction as Sentence Splitting
%A Vogel, Stephan
%S Proceedings of Machine Translation Summit X: Papers
%D 2005
%8 sep 13 15
%C Phuket, Thailand
%F vogel-2005-pesa
%X Most statistical machine translation systems use phrase-to-phrase translations to capture local context information, leading to better lexical choice and more reliable local reordering. The quality of the phrase alignment is crucial to the quality of the resulting translations. Here, we propose a new phrase alignment method, not based on the Viterbi path of word alignment models. Phrase alignment is viewed as a sentence splitting task. For a given spitting of the source sentence (source phrase, left segment, right segment) find a splitting for the target sentence, which optimizes the overall sentence alignment probability. Experiments on different translation tasks show that this phrase alignment method leads to highly competitive translation results.
%U https://aclanthology.org/2005.mtsummit-papers.33
%P 251-258
Markdown (Informal)
[PESA: Phrase Pair Extraction as Sentence Splitting](https://aclanthology.org/2005.mtsummit-papers.33) (Vogel, MTSummit 2005)
ACL