Adapting An Existing Example-Based Machine Translation (EBMT) System For New Language Pairs Based On An Optimized Bilingual Knowledge Bank (BKB).
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 Bilingua...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://eprints.usm.my/9394/1/Adapting_an_Existing_Example-Based_Machine_Translation_%28EBMT%29_System_for_New_Language_Pairs_based_on_an_Optimized_Bilingual_Knowledge_Bank_%28BKB%29.pdf http://eprints.usm.my/9394/ |
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| Summary: | 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.
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