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Pattern-Based Statistical Machine Translation for NTCIR-10 PatentMT

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

Abstract:

Pattern-based machine translation is a very traditional machine translation method that uses translation patterns and translation word (phrase) dictionaries. The characteristic of this translation method is that high-quality translation results can be obtained if the input sentence matches the translation pattern and this translation pattern is correct. However, translation patterns and translation word dictionaries are usually made manually. Therefore, there are many costs in making a pattern-based machine translation system.

We propose making translation patterns and translation word dictionaries automatically by using statistical machine translation methods. Using these methods, we decreased the costs in making a pattern-based machine translation system.

We demonstrate the effectiveness of the proposed method in a Japanese-English machine translation patent task (NTCIR-10). We obtained good results.