Adapting An Existing Example-Based Machine Translation (EBMT) System For New Language Pairs Based On An Optimized Bilingual Knowledge Bank (BKB).

Lim, Huan Ngee and Ye, Hong Hoe and Lim, Chai Kim and Tang, Enya Kong (2007) Adapting An Existing Example-Based Machine Translation (EBMT) System For New Language Pairs Based On An Optimized Bilingual Knowledge Bank (BKB). In: The 11th International Conference on Translation, November 2007, Kuala Lumpur , Malaysia.

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    Abstract

    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.

    Item Type: Conference or Workshop Item (Paper)
    Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
    Divisions: Pusat Pengajian Sains Komputer (School of Computer Sciences)
    Depositing User: ARKM Al Rashid Automasi
    Date Deposited: 21 Apr 2009 15:46
    Last Modified: 13 Jul 2013 12:08
    URI: http://eprints.usm.my/id/eprint/9394

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