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Pivot language approach for phrase-based statistical machine translation

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Machine Translation

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.

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Authors and Affiliations

  1. Toshiba (China) Research and Development Center, 501, Tower W2, Oriental Plaza, No. 1, East Chang An Ave., Dong Cheng District, Bei**g, 100738, China

    Hua Wu & Haifeng Wang

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  1. Hua Wu
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  2. Haifeng Wang
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Correspondence to Hua Wu.

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Wu, H., Wang, H. Pivot language approach for phrase-based statistical machine translation. Machine Translation 21, 165–181 (2007). https://doi.org/10.1007/s10590-008-9041-6

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  • DOI: https://doi.org/10.1007/s10590-008-9041-6

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