CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
A Character-Aware Encoder for Neural Machine Translation
Yang Z(杨振); Chen W(陈炜); Wang F(王峰); Chen W(陈伟)
Conference NameInternational Conference on Computational Linguistics
Conference Date2016-12-11
Conference Place日本大阪
AbstractThis article proposes a novel character-aware neural machine translation (NMT) model that views the input sequences as sequences of characters rather than words. On the use of row convolution (Amodei et al., 2015), the encoder of the proposed model composes word-level information from the input sequences of characters automatically. Since our model doesn’t rely on the boundaries between each word (as the whitespace boundaries in English), it is also applied to languages without explicit word segmentations (like Chinese). Experimental results on Chinese-English translation tasks show that the proposed character-aware NMT model can achieve comparable translation performance with the traditional word based NMT models. Despite the target side is still word based, the proposed model is able to generate much less unknown words.
Document Type会议论文
Corresponding AuthorChen W(陈伟)
First Author Affilication中国科学院自动化研究所
Recommended Citation
GB/T 7714
Yang Z,Chen W,Wang F,et al. A Character-Aware Encoder for Neural Machine Translation[C],2016.
Files in This Item: Download All
File Name/Size DocType Version Access License
coling2016.pdf(669KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang Z(杨振)]'s Articles
[Chen W(陈炜)]'s Articles
[Wang F(王峰)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang Z(杨振)]'s Articles
[Chen W(陈炜)]'s Articles
[Wang F(王峰)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang Z(杨振)]'s Articles
[Chen W(陈炜)]'s Articles
[Wang F(王峰)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: coling2016.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.