Improving English-to-Chinese Translation for Technical Terms using Morphological Information

Xianchao Wu, Naoaki Okazaki, Takashi Tsunakawa, Jun’ichi Tsujii


Abstract
The continuous emergence of new technical terms and the difficulty of keeping up with neologism in parallel corpora deteriorate the performance of statistical machine translation (SMT) systems. This paper explores the use of morphological information to improve English-to-Chinese translation for technical terms. To reduce the morpheme-level translation ambiguity, we group the morphemes into morpheme phrases and propose the use of domain information for translation candidate selection. In order to find correspondences of morpheme phrases between the source and target languages, we propose an algorithm to mine morpheme phrase translation pairs from a bilingual lexicon. We also build a cascaded translation model that dynamically shifts translation units from phrase level to word and morpheme phrase levels. The experimental results show the significant improvements over the current phrase-based SMT systems.
Anthology ID:
2008.amta-papers.19
Volume:
Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers
Month:
October 21-25
Year:
2008
Address:
Waikiki, USA
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
202–211
Language:
URL:
https://aclanthology.org/2008.amta-papers.19
DOI:
Bibkey:
Cite (ACL):
Xianchao Wu, Naoaki Okazaki, Takashi Tsunakawa, and Jun’ichi Tsujii. 2008. Improving English-to-Chinese Translation for Technical Terms using Morphological Information. In Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers, pages 202–211, Waikiki, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Improving English-to-Chinese Translation for Technical Terms using Morphological Information (Wu et al., AMTA 2008)
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PDF:
https://aclanthology.org/2008.amta-papers.19.pdf