A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task

Yusuke Oda, Katsuhito Sudoh, Satoshi Nakamura, Masao Utiyama, Eiichiro Sumita


Abstract
This paper describes the details about the NAIST-NICT machine translation system for WAT2017 English-Japanese Scientific Paper Translation Task. The system consists of a language-independent tokenizer and an attentional encoder-decoder style neural machine translation model. According to the official results, our system achieves higher translation accuracy than any systems submitted previous campaigns despite simple model architecture.
Anthology ID:
W17-5712
Volume:
Proceedings of the 4th Workshop on Asian Translation (WAT2017)
Month:
November
Year:
2017
Address:
Taipei, Taiwan
Venues:
WAT | WS
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
135–139
Language:
URL:
https://aclanthology.org/W17-5712
DOI:
Bibkey:
Cite (ACL):
Yusuke Oda, Katsuhito Sudoh, Satoshi Nakamura, Masao Utiyama, and Eiichiro Sumita. 2017. A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task. In Proceedings of the 4th Workshop on Asian Translation (WAT2017), pages 135–139, Taipei, Taiwan. Asian Federation of Natural Language Processing.
Cite (Informal):
A Simple and Strong Baseline: NAIST-NICT Neural Machine Translation System for WAT2017 English-Japanese Translation Task (Oda et al., 2017)
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PDF:
https://aclanthology.org/W17-5712.pdf