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Fast and extensible phrase scoring for Statistical Machine Translation
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Datorlingvistik)
2010 (English)In: Prague Bulletin of Mathematical Linguistics, ISSN 0032-6585, E-ISSN 1804-0462, no 93, 87-96 p.Article in journal (Refereed) Published
Abstract [en]

Existing tools for generating phrase tables for phrase-based Statistical Machine Translation (SMT) are generally optimised towards low memory use to allow processing of large corpora with limited memory. Whilst being a reasonable design choice, this approach does not make optimal use of resources when the sufficient memory is available. We present memscore, a new open-source tool to score phrases in memory. Besides acting as a faster drop-in replacement for existing software, it implements a number of standard smoothing techniques and provides a platform for easy experimentation with new scoring methods.

Place, publisher, year, edition, pages
Prague: Charles University, Institute of Formal and Applied Linguistics , 2010. no 93, 87-96 p.
National Category
Humanities
Identifiers
URN: urn:nbn:se:uu:diva-154487DOI: 10.2478v10108-010-0007-5OAI: oai:DiVA.org:uu-154487DiVA: diva2:420756
Note

In Proceedings of MT Marathon 2010, Dublin (http://www.mtmarathon2010.info/web/Welcome.html).

Available from: 2011-06-07 Created: 2011-06-05 Last updated: 2013-09-18Bibliographically approved

Open Access in DiVA

hardmeier:mt-marathon2010(135 kB)183 downloads
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Publisher's full texthttp://ufal.mff.cuni.cz/pbml/93/art-hardmeier.pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf