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  1. 論文誌(ジャーナル)
  2. Vol.53
  3. No.8

An Empirical Comparison of Parsers in Constraining Reordering for E-J Patent Machine Translation

https://ipsj.ixsq.nii.ac.jp/records/83474
https://ipsj.ixsq.nii.ac.jp/records/83474
afa91b84-01a3-409d-a647-0baf5a09c7f1
名前 / ファイル ライセンス アクション
IPSJ-JNL5308009.pdf IPSJ-JNL5308009 (530.2 kB)
Copyright (c) 2012 by the Information Processing Society of Japan
オープンアクセス
Item type Journal(1)
公開日 2012-08-15
タイトル
タイトル An Empirical Comparison of Parsers in Constraining Reordering for E-J Patent Machine Translation
タイトル
言語 en
タイトル An Empirical Comparison of Parsers in Constraining Reordering for E-J Patent Machine Translation
言語
言語 eng
キーワード
主題Scheme Other
主題 [一般論文] patent translation, parser, comparison, reordering constraint, English to Japanese
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者所属
National Institute of Information and Communications Technology
著者所属
National Institute of Information and Communications Technology
著者所属
National Institute of Information and Communications Technology
著者所属
National Institute of Information and Communications Technology
著者所属(英)
en
National Institute of Information and Communications Technology
著者所属(英)
en
National Institute of Information and Communications Technology
著者所属(英)
en
National Institute of Information and Communications Technology
著者所属(英)
en
National Institute of Information and Communications Technology
著者名 Isao, Goto

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Isao, Goto

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Masao, Utiyama

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Masao, Utiyama

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Takashi, Onishi

× Takashi, Onishi

Takashi, Onishi

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Eiichiro, Sumita

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Eiichiro, Sumita

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著者名(英) Isao, Goto

× Isao, Goto

en Isao, Goto

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Masao, Utiyama

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en Masao, Utiyama

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Takashi, Onishi

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en Takashi, Onishi

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Eiichiro, Sumita

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論文抄録
内容記述タイプ Other
内容記述 Machine translation of patent documents is very important from a practical point of view. One of the key technologies for improving machine translation quality is the utilization of syntax. It is difficult to select the appropriate parser for English to Japanese patent machine translation because the effects of each parser on patent translation are not clear. This paper provides an empirical comparative evaluation of several state-of-the-art parsers for English, focusing on the effects on patent machine translation from English to Japanese. We add syntax to a method that constrains the reordering of noun phrases for phrase-based statistical machine translation. There are two methods for obtaining the noun phrases from input sentences: 1) an input sentence is directly parsed by a parser and 2) noun phrases from an input sentence are determined by a method using the parsing results of the context document that contains the input sentence. We measured how much each parser contributed to improving the translation quality for each of the two methods and how much a combination of parsers contributed to improving the translation quality for the second method. We conducted experiments using the NTCIR-8 patent translation task dataset. Most of the parsers improved translation quality. Combinations of parsers using the method based on context documents achieved the best translation quality.

------------------------------
This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.4 (online)
DOI http://dx.doi.org/10.2197/ipsjjip.20.871
------------------------------
論文抄録(英)
内容記述タイプ Other
内容記述 Machine translation of patent documents is very important from a practical point of view. One of the key technologies for improving machine translation quality is the utilization of syntax. It is difficult to select the appropriate parser for English to Japanese patent machine translation because the effects of each parser on patent translation are not clear. This paper provides an empirical comparative evaluation of several state-of-the-art parsers for English, focusing on the effects on patent machine translation from English to Japanese. We add syntax to a method that constrains the reordering of noun phrases for phrase-based statistical machine translation. There are two methods for obtaining the noun phrases from input sentences: 1) an input sentence is directly parsed by a parser and 2) noun phrases from an input sentence are determined by a method using the parsing results of the context document that contains the input sentence. We measured how much each parser contributed to improving the translation quality for each of the two methods and how much a combination of parsers contributed to improving the translation quality for the second method. We conducted experiments using the NTCIR-8 patent translation task dataset. Most of the parsers improved translation quality. Combinations of parsers using the method based on context documents achieved the best translation quality.

------------------------------
This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.4 (online)
DOI http://dx.doi.org/10.2197/ipsjjip.20.871
------------------------------
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AN00116647
書誌情報 情報処理学会論文誌

巻 53, 号 8, 発行日 2012-08-15
ISSN
収録物識別子タイプ ISSN
収録物識別子 1882-7764
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