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Phrase-Based Statistical Machine Translation by Using Reordering Search and Additional Features

  • Miao Li
  • Peng Gao
  • Jian Zhang
  • Yi Luo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

The state of the art statistical machine translation (SMT) systems are based on phrase (a group of words), which are modeled using log-linear maximum entropy framework. In this paper, we constructed a phrase-based statistical machine translation system with additional feature models. The translation model is combined with four specific additional feature functions. When comparing our system with the baseline system of IWSLT2005, we can conclude that our system improve the SMT system accuracy with the same corpus.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Miao Li
    • 1
  • Peng Gao
    • 1
  • Jian Zhang
    • 1
  • Yi Luo
    • 1
  1. 1.Institute of Intelligent of Machines, China Academy of Sciences, AnhuiChina

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