Japanese-to-English patent translation system based on domain-adapted word segmentation and post-ordering

Katsuhito Sudoh, Masaaki Nagata, Shinsuke Mori, Tatsuya Kawahara


Abstract
This paper presents a Japanese-to-English statistical machine translation system specialized for patent translation. Patents are practically useful technical documents, but their translation needs different efforts from general-purpose translation. There are two important problems in the Japanese-to-English patent translation: long distance reordering and lexical translation of many domain-specific terms. We integrated novel lexical translation of domain-specific terms with a syntax-based post-ordering framework that divides the machine translation problem into lexical translation and reordering explicitly for efficient syntax-based translation. The proposed lexical translation consists of a domain-adapted word segmentation and an unknown word transliteration. Experimental results show our system achieves better translation accuracy in BLEU and TER compared to the baseline methods.
Anthology ID:
2014.amta-researchers.18
Volume:
Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track
Month:
October 22-26
Year:
2014
Address:
Vancouver, Canada
Editors:
Yaser Al-Onaizan, Michel Simard
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
234–248
Language:
URL:
https://aclanthology.org/2014.amta-researchers.18
DOI:
Bibkey:
Cite (ACL):
Katsuhito Sudoh, Masaaki Nagata, Shinsuke Mori, and Tatsuya Kawahara. 2014. Japanese-to-English patent translation system based on domain-adapted word segmentation and post-ordering. In Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track, pages 234–248, Vancouver, Canada. Association for Machine Translation in the Americas.
Cite (Informal):
Japanese-to-English patent translation system based on domain-adapted word segmentation and post-ordering (Sudoh et al., AMTA 2014)
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PDF:
https://preview.aclanthology.org/landing_page/2014.amta-researchers.18.pdf