Browse DORAS
Browse Theses
Latest Additions
Creative Commons License
Except where otherwise noted, content on this site is licensed for use under a:

Tracking relevant alignment characteristics for machine translation

Lambert, Patrik and Ma, Yanjun and Ozdowska, Sylwia and Way, Andy (2009) Tracking relevant alignment characteristics for machine translation. In: MT Summit XII - The twelfth Machine Translation Summit, 26-30 August 2009, Ottawa, Canada.

Full text available as:

[img]PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader


In most statistical machine translation (SMT) systems, bilingual segments are extracted via word alignment. In this paper we compare alignments tuned directly according to alignment F-score and BLEU score in order to investigate the alignment characteristics that are helpful in translation. We report results for two different SMT systems (a phrase-based and an n-gram-based system) on Chinese to English IWSLT data, and Spanish to English European Parliament data. We give alignment hints to improve BLEU score, depending on the SMT system used and the type of corpus.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:statistical machine translation;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 05/IN/1732, SFI 07/CE/I1142
ID Code:15161
Deposited On:15 Feb 2010 11:56 by DORAS Administrator. Last Modified 27 Apr 2010 11:34

Download statistics

Archive Staff Only: edit this record