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 deve...
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oai:animorepository.dlsu.edu.ph:faculty_research-29482022-07-07T02:42:47Z Philippine component of the network-based ASEAN language translation public service Nocon, Nicco Louis S. Oco, Nathaniel Ilao, Joel P. Roxas, Rachel Edita 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. © 2014 IEEE. 2014-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/1949 Faculty Research Work Animo Repository Machine translating--Southeast Asia Computer Sciences |
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Machine translating--Southeast Asia Computer Sciences Nocon, Nicco Louis S. Oco, Nathaniel Ilao, Joel P. Roxas, Rachel Edita Philippine component of the network-based ASEAN language translation public service |
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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. © 2014 IEEE. |
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text |
author |
Nocon, Nicco Louis S. Oco, Nathaniel Ilao, Joel P. Roxas, Rachel Edita |
author_facet |
Nocon, Nicco Louis S. Oco, Nathaniel Ilao, Joel P. Roxas, Rachel Edita |
author_sort |
Nocon, Nicco Louis S. |
title |
Philippine component of the network-based ASEAN language translation public service |
title_short |
Philippine component of the network-based ASEAN language translation public service |
title_full |
Philippine component of the network-based ASEAN language translation public service |
title_fullStr |
Philippine component of the network-based ASEAN language translation public service |
title_full_unstemmed |
Philippine component of the network-based ASEAN language translation public service |
title_sort |
philippine component of the network-based asean language translation public service |
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Animo Repository |
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2014 |
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https://animorepository.dlsu.edu.ph/faculty_research/1949 |
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1738854793940566016 |