Effectively training neural machine translation models with monolingual data
文献类型：期刊论文
| 作者 | Yang, Zhen1,2 ; Chen, Wei2; Wang, Feng2; Xu, Bo2
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2019-03-14 |
| 卷号 | 333页码:240-247 |
| 关键词 | Neural machine translation Monolingual data Gate-enhanced Source-side and target-side Effectively |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2018.12.032 |
| 通讯作者 | Yang, Zhen(yangzhen2014@ia.ac.cn) |
| 英文摘要 | Improving neural machine translation models (NMT) with monolingual data has aroused more and more interests in this area and back-translation for monolingual data augmentation Sennrich et al. (2016) has been taken as a promising development recently. While the naive back-translation approach improves the translation performance substantially, we notice that its usage for monolingual data is not so effective because traditional NMT models make no distinction between the true parallel corpus and the back translated synthetic parallel corpus. This paper proposes a gate-enhanced NMT model which makes use of monolingual data more effectively. The central idea is to separate the data flow of monolingual data and parallel data into different channels by the elegant designed gate, which enables the model to perform different transformations according to the type of the input sequence, i.e., monolingual data and parallel data. Experiments on Chinese-English and English-German translation tasks show that our approach achieves substantial improvements over strong baselines and the gate-enhanced NMT model can utilize the source-side and target-side monolingual data at the same time. (C) 2018 Elsevier B.V. All rights reserved. |
| WOS关键词 | NETWORK |
| 资助项目 | National Program on Key Basic Research Project of China (973 Program)[2013CB329302] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000456834100022 |
| 出版者 | ELSEVIER SCIENCE BV |
| 资助机构 | National Program on Key Basic Research Project of China (973 Program) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/25313]  |
| 专题 | 数字内容技术与服务研究中心_听觉模型与认知计算 |
| 通讯作者 | Yang, Zhen |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, 95 ZhongGuanCun East Rd, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Zhen,Chen, Wei,Wang, Feng,et al. Effectively training neural machine translation models with monolingual data[J]. NEUROCOMPUTING,2019,333:240-247. |
| APA | Yang, Zhen,Chen, Wei,Wang, Feng,&Xu, Bo.(2019).Effectively training neural machine translation models with monolingual data.NEUROCOMPUTING,333,240-247. |
| MLA | Yang, Zhen,et al."Effectively training neural machine translation models with monolingual data".NEUROCOMPUTING 333(2019):240-247. |
入库方式： OAI收割
来源：自动化研究所
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