Mining Japanese-Vietnamese multi-level parallel text corpus from Wikipedia data resource

Abstract

This paper presents the task of mining a Japanese - Vietnamese parallel text corpus from comparable data resources in application of machine translation. Data resource for this language pair is few and rare so the parallel text should be extracted at multi levels, sentence level and fragment level, to get as much data as possible. Moreover, the proposed method considers word order independently so it can be applied to different language families. The result applied on Japanese- Vietnamese Wikipedia resource shows that the proposed method increases significantly the number of extracted parallel data. The extracted multi-level parallel text contributes to the quality of machine translation as well. More than 144,000 pairs of parallel sentences and 148,000 pairs of parallel fragments had been mined and opened to the research community.