No Free Lunch in Factored Phrase-Based Machine Translation

  • Aleš Tamchyna
  • Ondřej Bojar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7817)


Factored models have been successfully used in many language pairs to improve translation quality in various aspects. In this work, we analyze this paradigm in an attempt at automating the search for well-performing machine translation systems. We examine the space of possible factored systems, concluding that a fully automatic search for good configurations is not feasible. We demonstrate that even if results of automatic evaluation are available, guiding the search is difficult due to small differences between systems, which are further blurred by randomness in tuning. We describe a heuristic for estimating the complexity of factored models. Finally, we discuss the possibilities of a “semi-automatic” exploration of the space in several directions and evaluate the obtained systems.


Machine Translation Generation Step Free Lunch Statistical Machine Translation Parallel Corpus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Aleš Tamchyna
    • 1
  • Ondřej Bojar
    • 1
  1. 1.Institute of Formal and Applied LinguisticsPrahaCzech Republic

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