An Improved Statistical Machine Translation Method for United Chinese-Japanese Word Segmentation

DOI

10.2991/iceeecs-16.2016.1How to use a DOI?

Keywords

machine translation; segmentation granularity; Kanji-Hanzi; Chinese-Japanese;

Abstract

As Chinese and Japanese word segmentation is processed with different tagging system and semantic performance, the granularity of word segmentation results should be readjusted to improve the performance of Statistical Machine Translation (SMT). This paper proposes an approach to adjust the word segmentation granularity for improving the performance of SMT, which combines Hanzi-Kanji comparison table and Japanese-Chinese dictionary. Experimental results express that the proposed method could adjust the granularity between Chinese and Japanese effectively and improve the performance of SMT.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaowei Wang
AU  - Jinke Wang
PY  - 2016/12
DA  - 2016/12
TI  - An Improved Statistical Machine Translation Method for United Chinese-Japanese Word Segmentation
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 1
EP  - 4
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.1
DO  - 10.2991/iceeecs-16.2016.1
ID  - Wang2016/12
ER  -