A Chinese-Japanese Lexical Machine Translation through a Pivot Language

  • Authors:

  • Takashi Tsunakawa;Naoaki Okazaki;Xiao Liu;Jun’ichi Tsujii

  • Affiliations:

  • University of Tokyo;University of Tokyo;University of Tokyo;University of Tokyo, University of Manchester, National Centre for Text Mining, UK

  • Venue:
  • ACM Transactions on Asian Language Information Processing (TALIP)
  • Year:
  • 2009

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Abstract

The bilingual lexicon is an expensive but critical resource for multilingual applications in natural language processing. This article proposes an integrated framework for building a bilingual lexicon between the Chinese and Japanese languages. Since the language pair Chinese-Japanese does not include English, which is a central language of the world, few large-scale bilingual resources between Chinese and Japanese have been constructed. One solution to alleviate this problem is to build a Chinese-Japanese bilingual lexicon through English as the pivot language. In addition to the pivotal approach, we can make use of the characteristics of Chinese and Japanese languages that use Han characters. We incorporate a translation model obtained from a small Chinese-Japanese lexicon and use the similarity of the hanzi and kanji characters by using the log-linear model. Our experimental results show that the use of the pivotal approach can improve the translation performance over the translation model built from a small Chinese-Japanese lexicon. The results also demonstrate that the similarity between the hanzi and kanji characters provides a positive effect for translating technical terms.