A noisy channel model for grapheme-based machine transliteration

Authors:
Yuxiang Jia;Danqing Zhu;Shiwen Yu
Affiliations:
Peking University, Beijing, China;Peking University, Beijing, China;Peking University, Beijing, China
Venue:
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Year:
2009

Citing 7
Cited 1

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Abstract

Machine transliteration is an important Natural Language Processing task. This paper proposes a Noisy Channel Model for Grapheme-based machine transliteration. Moses, a phrase-based Statistical Machine Translation tool, is employed for the implementation of the system. Experiments are carried out on the NEWS 2009 Machine Transliteration Shared Task English-Chinese track. English-Chinese back transliteration is studied as well.