Knowledge Commons of Institute of Automation,CAS
Synchronous Bidirectional Neural Machine Translation | |
Zhou, Long1,2![]() ![]() | |
发表期刊 | Transactions of Association for Computational Linguistics (TACL)
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2019 | |
期号 | Vol. 7页码:pp. 91-105 |
文章类型 | 自然语言处理顶级期刊 |
摘要 | Existing approaches to neural machine translation (NMT) generate the target language sequence token by token from left to right. However, this kind of unidirectional decoding framework cannot make full use of the target-side future contexts which can be produced in a right-to-left decoding direction, and thus suffers from the issue of unbalanced outputs. In this paper, we introduce a synchronous bidirectional neural machine translation (SB-NMT) that predicts its outputs using left-to-right and right-to-left decoding simultaneously and interactively, in order to leverage both of the history and future information at the same time. Specifically, we first propose a new algorithm that enables synchronous bidirectional decoding in a single model. Then, we present an interactive decoding model in which left-to-right (right-to-left) generation does not only depend on its previously generated outputs, but also relies on future contexts predicted by right-to-left (left-to-right) decoding. We extensively evaluate the proposed SB-NMT model on large-scale NIST Chinese-English, WMT14 English-German, and WMT18 Russian-English translation tasks. Experimental results demonstrate that our model achieves significant improvements over the strong Transformer model by 3.92, 1.49 and 1.04 BLEU points respectively, and obtains the state-of-the-art performance on Chinese-English and English-German translation tasks. |
关键词 | Neural machine translation, bidirectional decoding |
语种 | 英语 |
七大方向——子方向分类 | 自然语言处理 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39587 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
通讯作者 | Zhang, Jiajun |
作者单位 | 1.National Laboratory of Pattern Recognition, CASIA, Beijing, China 2.University of Chinese Academy of Sciences, Beijing, China 3.CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhou, Long,Zhang, Jiajun,Zong, Chenqqing. Synchronous Bidirectional Neural Machine Translation[J]. Transactions of Association for Computational Linguistics (TACL),2019(Vol. 7):pp. 91-105. |
APA | Zhou, Long,Zhang, Jiajun,&Zong, Chenqqing.(2019).Synchronous Bidirectional Neural Machine Translation.Transactions of Association for Computational Linguistics (TACL)(Vol. 7),pp. 91-105. |
MLA | Zhou, Long,et al."Synchronous Bidirectional Neural Machine Translation".Transactions of Association for Computational Linguistics (TACL) .Vol. 7(2019):pp. 91-105. |
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