UCSYNLP-Lab Machine Translation Systems for WAT 2019
This paper describes the UCSYNLP-Lab submission to WAT 2019 for Myanmar-English translation tasks in both direction. We have used the neural machine translation systems with attention model and utilized the UCSY-corpus and ALT corpus. In NMT with attention model, we use the word segmentation level as well as syllable segmentation level. Especially, we made the UCSY-corpus to be cleaned in WAT 2019. Therefore, the UCSY corpus for WAT 2019 is not identical to those used in WAT 2018. Experiments show that the translation systems can produce the substantial improvements.
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