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Statistical analysis of alignment characteristics for phrase-based machine translation

Lambert, Patrik and Petitrenaud, Simon and Ma, Yanjun and Way, Andy (2010) Statistical analysis of alignment characteristics for phrase-based machine translation. In: EAMT 2010 - 14th Annual Conference of the European Association for Machine Translation, 27-28 May 2010, Saint-Raphaël, France.

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In most statistical machine translation (SMT) systems, bilingual segments are extracted via word alignment. However, there lacks systematic study as to what alignment characteristics can benefit MT under specific experimental settings such as the language pair or the corpus size. In this paper we produce a set of alignments by directly tuning the alignment model according to alignment F-score and BLEU score in order to investigate the alignment characteristics that are helpful in translation. We report results for a phrasebased SMT system on Chinese-to-English IWSLT data, and Spanish-to-English European Parliament data. With a statistical analysis into alignment characteristics that are correlated with BLEU score, we give alignment hints to improve BLEU score using a phrase-based SMT system and different types of corpus.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Published in:Proceedings of the 14th Annual Conference of the EAMT. . European Association for Machine Translation.
Publisher:European Association for Machine Translation
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15790
Deposited On:09 Nov 2010 17:08 by Shane Harper. Last Modified 09 Nov 2010 17:08

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