Abstract

Information exchange is increasing rapidly with the advent of globalization. As the language spoken by the most people in today's world, Chinese will play an important role in information exchange in the future. Therefore, we need an efficient and practical means to access the increasingly large volume of Chinese data. This thesis describes a target-dominant Chinese-English machine translation system, which can translate a given Chinese news sentence into English. We conjecture that we can improve the state of the art of MT using a TDMT approach. This system has participated in the NIST (National Institute of Standards and Technology) 2004 machine translation competition. Experimental results on Penn Chinese Treebank corpus show that a machine translation system adopting a target-dominant approach is promising.

Degree

MS

College and Department

Physical and Mathematical Sciences; Computer Science

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2004-11-23

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd609

Keywords

target-dominant, Chinese-English, machine translation, Chinese-English machine translation, TDMT, HALogen generator, HALogen converter, HALogen translation, target expertise

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