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Machine Translation

13th China Workshop, CWMT 2017, Dalian, China, September 27-29, 2017, Revised Selected Papers

  • Derek F. Wong
  • Deyi Xiong
Conference proceedings CWMT 2017

Part of the Communications in Computer and Information Science book series (CCIS, volume 787)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Yachao Li, Deyi Xiong, Min Zhang
    Pages 1-8
  3. Kenan Li, Heyan Huang, Yuhang Guo, Ping Jian
    Pages 9-19
  4. Shaotong Li, JinAn Xu, Yujie Zhang, Yufeng Chen
    Pages 20-29
  5. Yining Wang, Long Zhou, Jiajun Zhang, Chengqing Zong
    Pages 30-42
  6. Guoyi Miao, Jinan Xu, Yancui Li, Shaotong Li, Yufeng Chen
    Pages 43-54
  7. Hongjie Ji, Shujian Huang, Qi Hou, Cunyan Yin, Jiajun Chen
    Pages 55-67
  8. Hui Yu, Weizhi Xu, Shouxun Lin, Qun Liu
    Pages 68-77
  9. Liang Ding, Yanqing He, Lei Zhou, Qingmin Liu
    Pages 90-101
  10. Fuxue Li, Du Quan, Wang Qiang, Xiao Tong, Jingbo Zhu
    Pages 102-111
  11. Yirong Pan, Xiao Li, Yating Yang, Chenggang Mi, Rui Dong, Wenxiao Zeng
    Pages 112-123
  12. Back Matter
    Pages 125-125

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 13th China Workshop on Machine Translation, CWMT 2017, held in Dalian, China, in September 2017.
The 10 papers presented in this volume were carefully reviewed and selected from 26 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.

Keywords

Natural Language Processing Machine Translation Neural Machines Translation Statistical Machine Translation Deep Learning

Editors and affiliations

  • Derek F. Wong
    • 1
  • Deyi Xiong
    • 2
  1. 1.University of MacauMacau SARChina
  2. 2.Soochow UniversitySuzhouChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-7134-8
  • Copyright Information Springer Nature Singapore Pte Ltd. 2017
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-10-7133-1
  • Online ISBN 978-981-10-7134-8
  • Series Print ISSN 1865-0929
  • Series Online ISSN 1865-0937
  • Buy this book on publisher's site
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