Allan Borra

Computational linguistics research on Philippine languages

This is a paper that describes computational linguistic activities on Philippines languages. The Philippines is an archipelago with vast numbers of islands and numerous languages. The tasks of understanding, representing and implementing these languages require enormous work. An extensive amount of work has been done on understanding at least some of the major Philippine languages, but little has been done on the computational aspect. Majority of the latter has been on the purpose of machine translation.

Building language resources for a Multi-Engine English-Filipino machine translation system

In this paper, we present the building of various language resources for a multi-engine bi-directional English-Filipino Machine Translation (MT) system. Since linguistics information on Philippine languages are available, but as of yet, the focus has been on theoretical linguistics and little is done on the computational aspects of these languages, attempts are reported here on the manual construction of these language resources such as the grammar, lexicon, morphological information, and the corpora which were literally built from almost non-existent digital forms. Due to the inherent difficulties of manual construction, we also discuss our experiments on various technologies for automatic extraction of these resources to handle the intricacies of the Filipino language, designed with the intention of using them for the MT system. To implement the different MT engines and to ensure the improvement of translation quality, other language tools (such as the morphological analyzer and generator, and the part of speech tagger) were developed.

A corpus-based analysis of Filipino writing errors

This study presents the common grammatical and spelling errors made by Filipino native speakers through corpus-based analysis. A total of 8,000 sentences of student translation exercises were collected and analyzed using manual and computational means. A total of 1,413 errors surfaced that were categorized into eight error types namely: use of ligatures, spelling error, use of enclitics, translation errors, hyphenation, use of function words “nang” and “ng”, morphophonemic errors, and word repetition. The study concludes that the top 3 common errors are the use of ligatures such as “na”, /-ng/ and /-g/ (46.6%), spelling errors such as incorrectly merging of different words (19.5%), and use of enclitics such as “daw” and “raw” (16.1%). For future works, theoretical framework will be considered when analyzing the errors.