Adapting An Existing Example-Based Machine Translation (EBMT) System For New Language Pairs Based On An Optimized Bilingual Knowledge Bank (BKB). - Lim, Huan Ngee; Ye, Hong Hoe; Lim, Chai Kim; Tang, Enya Kong (2007)

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Sourcing for large amount of text and translating them are some of the challenges in building an Example-Based Machine Translation (EBMT) system. These big amounts of translated texts are annotated into the S-SSTC format to cover an extensive vocabulary and sentence structures. However, the Bilingual Knowledge Bank (BKB), which is a collection of the S-SSTCs, will normally contain redundancy. Hence, the idea of an optimized BKB is born. An optimized BKB (redundancy reduced; is smaller in size but is as equally extensive in term of its sentence structure coverage compared to an un-optimized BKB. Therefore, an optimized BKB enhances the performance of the EBMT. In this paper, we introduce the idea of an optimized BKB and propose it to be re-used to effectively construct new BKBs in order to adapt an existing EBMT for new language pairs.