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  • 标题:Otedama: Fast Rule-Based Pre-Ordering for Machine Translation
  • 本地全文:下载
  • 作者:Julian Hitschler ; Laura Jehl ; Sariya Karimova
  • 期刊名称:The Prague Bulletin of Mathematical Linguistics
  • 印刷版ISSN:0032-6585
  • 电子版ISSN:1804-0462
  • 出版年度:2016
  • 卷号:106
  • 期号:1
  • 页码:159-168
  • DOI:10.1515/pralin-2016-0015
  • 语种:English
  • 出版社:Walter de Gruyter GmbH
  • 摘要:We present Otedama, a fast, open-source tool for rule-based syntactic pre-ordering, a well established technique in statistical machine translation. Otedama implements both a learner for pre-ordering rules, as well as a component for applying these rules to parsed sentences. Our system is compatible with several external parsers and capable of accommodating many source and all target languages in any machine translation paradigm which uses parallel training data. We demonstrate improvements on a patent translation task over a state-of-the-art English-Japanese hierarchical phrase-based machine translation system. We compare Otedama with an existing syntax-based pre-ordering system, showing comparable translation performance at a runtime speedup of a factor of 4.5-10.
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