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Statistical Machine Translation of German Compound Words

  • Maja Popović
  • Daniel Stein
  • Hermann Ney
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4139)

Abstract

German compound words pose special problems to statistical machine translation systems: the occurence of each of the components in the training data is not sufficient for successful translation. Even if the compound itself has been seen during training, the system may not be capable of translating it properly into two or more words. If German is the target language, the system might generate only separated components or may not be capable of choosing the correct compound. In this work, we investigate and compare different strategies for the treatment of German compound words in statistical machine translation systems. For translation from German, we compare linguistic-based and corpus-based compound splitting. For translation into German, we investigate splitting and rejoining German compounds, as well as joining English potential components. Additionaly, we investigate word alignments enhanced with knowledge about the splitting points of German compounds. The translation quality is consistently improved by all methods for both translation directions.

Keywords

Target Language Compound Word Training Corpus Translation Direction Statistical Machine Translation 
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 2006

Authors and Affiliations

  • Maja Popović
    • 1
  • Daniel Stein
    • 1
  • Hermann Ney
    • 1
  1. 1.Lehrstuhl für Informatik VI – Computer Science DepartmentRWTH Aachen UniversityAachenGermany

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