Philippine component of the network-based ASEAN language translation public service

Communication between different nations is essential. Languages which are foreign to another impose difficulty in understanding. For this problem to be resolved, options are limited to learning the language, having a dictionary as a guide, or making use of a translator. This paper discusses the development of ASEANMT-Phil, a phrase-based statistical machine translator, to be utilized as a tool beneficial for assisting ASEAN countries. The data used for training and testing came from Wikipedia articles comprising of 124,979 and 1,000 sentence pairs, respectively. ASEANMT-Phil was experimented on different settings producing the BLEU score of 32.71 for Filipino-English and 31.15 for English-Filipino. Future Directions for the translator includes the following: improvement of data through changing or adding the domain or size; implementing an additional approach; and utilizing a larger dictionary to the approach.