POS-based reordering rules for Indonesian-Korean statistical machine translation

In SMT system, reordering problem is one of the most important and difficult problems to solve. The problem becomes definitely serious due to the different grammatical pattern between source and target language. The previous research about reordering model in SMT use the distortion-based reordering approach. However, this approach is not suitable for Indonesian-Korean translation. The main reason is because the word order between Indonesian and Korean are mostly reversed. Therefore, in this study, we develop a source-side reordering rules by using POS tag and word alignment information. This technique is promising to solve the reordering problem based on the experimental result. By applying 130 reordering rules in ID-KR and 50 reordering rules for KR-ID translation, the quality of translation in term of BLEU score increases 1.25% for ID-KR translation and 0.83% for KR-ID translation. Besides, combining this reordering rules with Korean verb formation rules for ID-KR translation can increase the BLEU score from 38.07 to 49.46 (in 50 simple sentences evaluation).