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Neural Machine Translation Model with a Large Vocabulary Selected by Branching Entropy., , , and . CoRR, (2017)TSUKU Statistical Machine Translation System for the NTCIR-10 PatentMT Task., , , , and . NTCIR, National Institute of Informatics (NII), (2013)An Efficient Language Model Using Double-Array Structures., , , and . EMNLP, page 222-232. ACL, (2013)Neural Machine Translation Model with a Large Vocabulary Selected by Branching Entropy., , , , and . MTSummit (1), page 227-240. (2017)Evaluating Features for Identifying Japanese-Chinese Bilingual Synonymous Technical Terms from Patent Families., , , and . BUCC@ACL/IJCNLP, page 52-61. Association for Computational Linguistics, (2015)Inter-, Intra-, and Extra-Chunk Pre-Ordering for Statistical Japanese-to-English Machine Translation., , , and . ACM Trans. Asian & Low-Resource Lang. Inf. Process., 15 (3): 20:1-20:28 (2016)Topic-based language models using Dirichlet Mixtures., , and . Syst. Comput. Jpn., 38 (12): 76-85 (2007)An Unsupervised Parameter Estimation Algorithm for a Generative Dependency N-gram Language Model., and . IJCNLP, page 516-524. Asian Federation of Natural Language Processing / ACL, (2013)To filter discontinuous word alignment for statistical machine translationaper., and . ICAILP, page 449-453. IEEE, (2014)Constructing family trees of multilingual speech using Gaussian mixture models., , and . INTERSPEECH, page 2253-2256. ISCA, (2005)