Improving Arabic-Chinese statistical machine translation using English as pivot language

Authors:
Nizar Habash;Jun Hu
Affiliations:
Columbia University, New York, NY;Columbia University, New York, NY
Venue:
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Year:
2009

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Abstract

We present a comparison of two approaches for Arabic-Chinese machine translation using English as a pivot language: sentence pivoting and phrase-table pivoting. Our results show that using English as a pivot in either approach outperforms direct translation from Arabic to Chinese. Our best result is the phrase-pivot system which scores higher than direct translation by 1.1 BLEU points. An error analysis of our best system shows that we successfully handle many complex Arabic-Chinese syntactic variations.