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Item
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Statistical Machine Translation between Myanmar and Myeik
http://hdl.handle.net/20.500.12678/0000004586
http://hdl.handle.net/20.500.12678/00000045861a47cbf5-928b-42d0-8e82-e9a3266a40fb
5e74f524-668e-488a-af08-eb1869d573e7
Name / File | License | Actions |
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Statistical Machine Translation between Myanmar and Myeik | |||||
Language | en | |||||
Publication date | 2020-02-28 | |||||
Authors | ||||||
Oo, Thazin Myint | ||||||
Thu, Ye Kyaw | ||||||
Soe, Khin Mar | ||||||
Supnithi, Thepchai | ||||||
Description | ||||||
This paper contributes the first evaluation of the quality of machine translation betweenMyanmar and Myeik (also known as Beik) . We also developed a Myanmar-Myeik parallel corpus (around10K sentences) based on the Myanmar language of ASEAN MT corpus. In addition, two types ofsegmentation were studied word and syllable segmentation. The 10 folds cross-validation experiments werecarried out using three different statistical machine translation approaches: phrase-based, hierarchical phrasebased, and the operation sequence model (OSM). The results show that all three statistical machinetranslation approaches give higher and comparable BLEU and RIBES scores for both Myanmar to Myeik andMyeik to Myanmar machine translations. OSM approach achieved the highest BLEU and RIBES scoresamong three approaches. We also found that syllable segmentation is appropriate for translation qualitycomparing with word level segmentation results. | ||||||
Keywords | ||||||
Statistical machine translation, Myanmar language (Burmese), Myeik dialect, Machine translation for dialects, Parallel corpus developing | ||||||
Identifier | 978-981-14-4787-7 | |||||
Journal articles | ||||||
Proceedings of the 10th International Workshop on Computer Science and Engineering (WCSE 2020) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |