![]() ![]() Anthology ID: D19-5206 Volume: Proceedings of the 6th Workshop on Asian Translation Month: November Year: 2019 Address: Hong Kong, China Editors: Toshiaki Nakazawa, We also investigated the feasibility of unsupervised machine translation for low-resource and distant language pairs and confirmed observations of previous work showing that unsupervised MT is still largely unable to deal with them. Our combination of NMT and SMT performed among the best systems for the four translation directions. For all the translation directions, we built state-of-the-art supervised neural (NMT) and statistical (SMT) machine translation systems, using monolingual data cleaned and normalized. Abstract This paper presents the NICT’s supervised and unsupervised machine translation systems for the WAT2019 Myanmar-English and Khmer-English translation tasks. ![]()
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