Translating Chinese Unknown Words by Automatically Acquired Templates
Ming-Hong Bai, Yu‐Ming Hsieh, Keh-Jiann Chen, Jason S. Chang · International Joint Conference on Natural Language Processing · 2013
In this paper, we present a translation template model to translate Chinese unknown words. The model exploits translation templates, which are extracted automatically from a word-aligned parallel corpus, to translate unknown words. The translation templates are designed in accordance with the structure of unknown words. When an unknown word is detected during translation, the model applies translation templates to the word to get a set of matched templates, and then translates the word into a set of suggested translations. Our experiment results demonstrate that the translations suggested by the unknown word translation template model significantly improve the performance of the Moses machine translation system.