The CMU-EBMT machine translation system
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- 作者：Ralf D. Brown (1) ralf@cs.cmu.edu
- 关键词：Open source software – ; Example ; based machine translation – ; Parameter tuning
- 刊名：Machine Translation
- 出版时间：June 2011
- 出版年：2011
- 期刊代码：36_09226567
- 类别：cp
- 卷：25
- 期：2
- 页码：179-195
- 数据来源：sp
摘要
This paper presents an in-depth description of the features of the open-source CMU-EBMT example-based machine translation system. CMU-EBMT is a complete end-to-end system including lexicon induction, word and phrase alignment, corpus indexing and lookup, language model, decoder, and parameter tuning components. While it does not require them, it can take advantage of external alignment information and other annotations provided by GIZA++ and other systems. To illustrate a recent addition to CMU-EBMT, experiments are presented which show an improvement of 0.16 BLEU points (0.9%relative) on a cross-validated small-data English–Haitian translation task when using a new set of fine-grained log-linear feature values representing language model match lengths in addition to language model probabilities.