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Improved Neural Machine Translation with Chinese Phonologic Features

  • Harbin Institute of Technology
  • Microsoft Researcher Asian

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Chinese phonologic features play an important role not only in the sentence pronunciation but also in the construction of a native Chinese sentence. To improve the machine translation performance, in this paper we propose a novel phonology-aware neural machine translation (PA-NMT) model where Chinese phonologic features are leveraged for translation tasks with Chinese as the target. A separate recurrent neural network (RNN) is constructed in NMT framework to exploit Chinese phonologic features to help facilitate the generation of more native Chinese expressions. We conduct experiments on two translation tasks: English-to-Chinese and Japanese-to-Chinese tasks. Experimental results show that the proposed method significantly outperforms state-of-the-art baselines on these two tasks.

源语言英语
主期刊名Natural Language Processing and Chinese Computing - 7th CCF International Conference, NLPCC 2018, Proceedings
编辑Dongyan Zhao, Sujian Li, Min Zhang, Vincent Ng, Hongying Zan
出版商Springer Verlag
303-315
页数13
ISBN(印刷版)9783319994949
DOI
出版状态已出版 - 2018
活动7th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2018 - Hohhot, 中国
期限: 26 8月 201830 8月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11108 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议7th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2018
国家/地区中国
Hohhot
时期26/08/1830/08/18

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