A Novel Approach for Handling Unknown Word Problem in Chinese-Vietnamese Machine Translation

For languages where space cannot be a boundary of a word, such as Chinese and Vietnamese, word segmentation is always the task to be done first in a statistical machine translation system (SMT). The word segmentation increases the translation quality, but it causes many unknown words (UKW) in the target translation. In this paper, we will present a novel approach to translate UKW. Based on the meaning relationship between Chinese and Vietnamese, we built a model which based on the meaning of the characters forming the UKW before translating the UKW through the model. Experiments show that our method significantly improved the performance of SMT.