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Statistical Machine Translation adding Rule based Machine Translation

Jin'ichi Murakami
Department of Information and Knowledge Engineering Faculty of Engineering
4-101 koyamachou Tottori City
ikehara@ike.tottori-u.ac.jp

概要:

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 Japanese-English machine translation, first, we used a Japanese-English rule-based MT, and we obtained "ENGLISH" sentences from Japanese 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 0.2565 in the Intrinsic-JE task using our proposed method. In contrast, we obtained a BLEU score of 0.2165 in the Intrinsic-JE task using a standard method (moses). And we obtained a BLEU score of 0.2602 in the Intrinsic-EJ task using our proposed method. In contrast, we obtained a BLEU score of 0.2501 in the Intrinsic-EJ task using a standard method (moses).

This means that our proposed method was effective for the Intrinsic-JE and Intrinsic-EJ task. For the future study, we will try to improve the performance by optimizing parameters.

I.2.7 Natural Language Processing Machine translation

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