A Detailed Analysis of Phrase-based and Syntax-based Machine Translation: The Search for Systematic Differences

نویسندگان

  • Rasoul Samad Zadeh Kaljahi
  • Raphael Rubino
  • Johann Roturier
  • Jennifer Foster
چکیده

This paper describes a range of automatic and manual comparisons of phrase-based and syntax-based statistical machine translation methods applied to English-German and English-French translation of user-generated content. The syntax-based methods underperform the phrase-based models and the relaxation of syntactic constraints to broaden translation rule coverage means that these models do not necessarily generate output which is more grammatical than the output produced by the phrase-based models. Although the systems generate different output and can potentially be fruitfully combined, the lack of systematic difference between these models makes the combination task more challenging.

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تاریخ انتشار 2012