Rule extraction applied in language translation (REAL) translation
Date of Publication
2006
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Michelle Wendy Tan
Defense Panel Member
Allan B. Borra
Rachel Edita O. Roxas
Charibeth Ko Cheng
Abstract/Summary
The most common approaches in Machine Translation are the rule-based and example-based approaches. The rule-based approach yields high quality results but it relies predetermined linguistic resources, which requires much human labor (Bond, et. Al., 1997). While the example-based approach, although an effective paradigm by itself, can only operate on domain-specific languages, and is highly data dependent (Bond, et. Al., 1997).
Thus, an English-Filipino MT system, TWiRL (Ang, et. Al., 2005), was developed. TWiRL used the rule-based approach with an integration of machine learning of rules to allow flexibility in translation. However, the system itself contains limitations, most notably, it translates only a subset of the English language.
This research recited some of the limitation of TWiRL. Also, an there is little exploration of rule-based with rule learning approaches in MT with Filipino as source and English as target languages, this research focused on translating Filipino texts to English. As a result, a system that is able to learn transfer rules by analyzing learning corpora, and use the rules to translate English to Filipino texts and vice versa was constructed. However, development of more accurate linguistic resources such as POS taggers and morphological analyzers are recommended by this research."
Abstract Format
html
Language
English
Format
Accession Number
TU14650
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Recommended Citation
Alcantara, D. L., Hong, B. S., Perez, A. L., & Tan, L. C. (2006). Rule extraction applied in language translation (REAL) translation. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14437