Vietnamese to Chinese Machine Translation via Chinese Character as Pivot

Using Chinese characters as an intermediate equivalent unit, we decompose machine translation into two stages, semantic translation and grammar translation. This strategy is tentatively applied to machine translation between Vietnamese and Chinese. During the semantic translation, Vietnamese syllables are one-by-one converted into the corresponding Chinese characters. During the grammar translation, the sequences of Chinese characters in Vietnamese grammar order are modified and rearranged to form grammatical Chinese sentence. Compared to the existing single alignment model, the division of two-stage processing is more targeted for research and evaluation of machine translation. The proposed method is evaluated using the standard BLEU score and a new manual evaluation metric, understanding rate. Only based on a small number of dictionaries, the proposed method gives competitive and even better results compared to existing systems.