We have developed a two-stage machine translation (MT) system. The first stage is a rule-based machine translation system. The second stage is a normal statistical machine translation system. For Chinese-English machine translation, first, we used a Chinese-English rule-based MT, and we obtained "ENGLISH" sentences from Chinese sentences. Second, we used a standard statistical machine translation. This means that we translated "ENGLISH" to English machine translation. We believe this method has two advantages. One is that there are fewer unknown words. The other is that it produces structured or grammatically correct sentences.
From the results of experiments, we obtained a BLEU score of 0.3151 in the BTEC-CE task using our proposed method. In contrast, we obtained a BLEU score of 0.3311 in the BTEC-CE task using a standard method (moses). This means that our proposed method was not as effective for the BTEC-CE task. Therefore, we will try to improve the performance by optimizing parameters.
-gram Language Model