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Machine Translation

, Volume 21, Issue 3, pp 165–181 | Cite as

Pivot language approach for phrase-based statistical machine translation

  • Hua Wu
  • Haifeng Wang
Article

Abstract

This paper proposes a novel method for phrase-based statistical machine translation based on the use of a pivot language. To translate between languages L s and L t with limited bilingual resources, we bring in a third language, L p , called the pivot language. For the language pairs L s  − L p and L p  − L t , there exist large bilingual corpora. Using only L s  − L p and L p  − L t bilingual corpora, we can build a translation model for L s  − L t . The advantage of this method lies in the fact that we can perform translation between L s and L t even if there is no bilingual corpus available for this language pair. Using BLEU as a metric, our pivot language approach significantly outperforms the standard model trained on a small bilingual corpus. Moreover, with a small L s  − L t bilingual corpus available, our method can further improve translation quality by using the additional L s  − L p and L p  − L t bilingual corpora.

Keywords

Pivot language Phrase-based statistical machine translation Scarce bilingual resources 

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Toshiba (China) Research and Development CenterBeijingChina

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