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Improved Arabic-French Machine Translation through Preprocessing Schemes and Language Analysis

  • Fatiha Sadat
  • Emad Mohamed
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7884)

Abstract

Arabic is a morphologically rich and complex language, which presents significant challenges for natural language processing and machine translation. In this paper, we describe an ongoing effort to build a competitive Arabic–French statistical machine translation system using the Moses decoder and other tools. The results show a significant increase in terms of Bleu score by introducing some preprocessing schemes for Arabic in addition to other language analysis rules.

Keywords

Arabic morphology statistical machine translation comparable corpora parallel corpora pre-processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Fatiha Sadat
    • 1
  • Emad Mohamed
    • 1
  1. 1.MontrealCanada

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