Building a Filipino colloquialism translator using sequence-to-sequence model

• Main Authors: Nocon, Nicco Louis S., Kho, Nyssa Michelle D., Arroyo, Jeniffer
• Format: text
• Published: Animo Repository 2018
• Subjects: Machine translating; Colloquial language > Translating; Filipino language > Spoken Filipino > Translating; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/66
• Institution: De La Salle University

Colloquialism in the Philippines has been prominently used in day-to-day conversations. Its vast emergence is evident especially on social media platforms but poses issues in terms of understandability to certain groups. For this research, machine translators have been implemented to fill in that gap. The translators cover Filipino Textspeak or Shortcuts, Swardspeak or Gay-lingo, Conyo, and Datkilab-implemented on Tensorflow library and Moses tool. Implementing in Tensorflow achieved 85.88 BLEU score when evaluated to the training data and 14.67 to the test data, while Moses garnered 95.27 BLEU score on training data and 79.91 on test data. Analyses on both implementations include advantages and disadvantages in using each one. Through the analyses and development of this research, it is recommended to implement the following in the future: addition of colloquialism samples, experimentation on sequence-to-sequence configurations, applying Graphical User Interface (GUI) to the translators, implementing the translators to Natural Language Processing (NLP) tools, and to deploy the translators as a web application.