Hybrid Filipino-English machine translation system

Approaches in machine translation in the past have been generally classified as either knowledge-based or corpus-based. It has been evident from the inception of machine translation to the present day, that utilizing a single approach, albeit knowledge-based or corpus-based, is not enough to fulfill...

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Bibliographic Details
Main Authors: Fontanilla, Gian Kristian A., Roxas, Rachel Edita O.
Format: text
Published: Animo Repository 2008
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/5122
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Institution: De La Salle University
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Summary:Approaches in machine translation in the past have been generally classified as either knowledge-based or corpus-based. It has been evident from the inception of machine translation to the present day, that utilizing a single approach, albeit knowledge-based or corpus-based, is not enough to fulfill the needs of a modern-day machine translation system. In order to address these issues, an amalgamation of approaches is explored to exploit the advantages of both approaches. The hybrid system learns both transfer rules and translation templates from a given training set. Unification constraints are also learned alongside transfer rules, which preserve subject-verb agreement and other linguistic phenomena during translation, which was previously unhandled by its rule-based predecessor.