Building a bilingual lexicon using phrase-based statistical machine translation via a pivot language

Takashi Tsunakawa, Naoaki Okazaki, Jun'ichi Tsujii

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper proposes a novel method for building a bilingual lexicon through a pivot language by using phrase-based statistical machine translation (SMT). Given two bilingual lexicons between language pairs Lf-Lp and Lp-Le, we assume these lexicons as parallel corpora. Then, we merge the extracted two phrase tables into one phrase table between Lf and Le. Finally, we construct a phrase-based SMT system for translating the terms in the lexicon Lf-Lp into terms of Le and, obtain a new lexicon Lf-Le. In our experiments with Chinese-English and Japanese-English lexicons, our system could cover 72.8% of Chinese terms and drastically improve the utilization ratio.

Original languageEnglish
Title of host publicationColing 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference
Pages127-130
Number of pages4
Publication statusPublished - 2008 Dec 1
Event22nd International Conference on Computational Linguistics, Coling 2008 - Manchester, United Kingdom
Duration: 2008 Aug 182008 Aug 22

Publication series

NameColing 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference
Volume1

Other

Other22nd International Conference on Computational Linguistics, Coling 2008
CountryUnited Kingdom
CityManchester
Period08/8/1808/8/22

ASJC Scopus subject areas

  • Language and Linguistics
  • Computational Theory and Mathematics
  • Linguistics and Language

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