Aye Thida

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2019

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UCSMNLP: Statistical Machine Translation for WAT 2019
Aye Thida | Nway Nway Han | Sheinn Thawtar Oo | Khin Thet Htar
Proceedings of the 6th Workshop on Asian Translation

This paper represents UCSMNLP’s submission to the WAT 2019 Translation Tasks focusing on the Myanmar-English translation. Phrase based statistical machine translation (PBSMT) system is built by using other resources: Name Entity Recognition (NER) corpus and bilingual dictionary which is created by Google Translate (GT). This system is also adopted with listwise reranking process in order to improve the quality of translation and tuning is done by changing initial distortion weight. The experimental results show that PBSMT using other resources with initial distortion weight (0.4) and listwise reranking function outperforms the baseline system.

2018

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Statistical Machine Translation Using 5-grams Word Segmentation in Decoding
Aye Thida | Nway Nway Han | Sheinn Thawtar Oo
Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation: 5th Workshop on Asian Translation: 5th Workshop on Asian Translation

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