Extraction of Potentially Useful Phrase Pairs for Statistical Machine Translation (Preprint)

• Juan Luo

  Graduate School of Information, Production and Systems, Waseda University

• Yves Lepage

  Graduate School of Information, Production and Systems, Waseda University

抄録

Over the last decade, an increasing amount of work has been done to advance the phrase-based statistical machine translation model in which the method of extracting phrase pairs consists of word alignment and phrase extraction. In this paper, we show that, for Japanese-English and Chinese-English statistical machine translation systems, this method is indeed missing potentially useful phrase pairs which could lead to better translation scores. These potentially useful phrase pairs can be detected by looking at the segmentation traces after decoding. We choose to see the problem of extracting potentially useful phrase pairs as a two-class classification problem: among all the possible phrase pairs, distinguish the useful ones from the not-useful ones. As for any classification problem, the question is to discover the relevant features which contribute the most. Extracting potentially useful phrase pairs resulted in a statistically significant improvement of 7.65 BLEU points in English-Chinese and 7.61 BLEU points in Chinese-English experiments. A slight increase of 0.94 BLEU points and 0.4 BLEU points is also observed for English-Japanese system and Japanese-English system, respectively.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.23(2015) No.3 (online)------------------------------

収録刊行物

• 情報処理学会論文誌

  情報処理学会論文誌 56 (4), 2015-04-15

  一般社団法人情報処理学会

キーワード

• [一般論文] statistical machine translation, phrase table, classification model

詳細情報

• CRID: 1570854177857957760
• NII論文ID: 110009890370
• NII書誌ID: AN00116647
• ISSN: 03875806
• 本文言語コード: en
• データソース種別:
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