Papers by Kazunori Yamaguchi

1 papers
Compact and Robust Models for Japanese-English Character-level Machine Translation (D19-52)

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Challenge: In recent years, neural machine translation (NMT) has made a great progress, and its translation quality has far surpassed the conventional statistical machine translation.
Approach: They propose a character-level translation model which is mid-gated and multi-attention model for Japanese-English translation and propose to train them using a relatively narrow beam of width 4 or 5 .
Outcome: The proposed models can translate the word containing Katakana by coining out a close word, and the model can produce tolerable results for noised sentences.

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