Type

Conference Proceedings

Authors

Qun Liu
Andy Way
Zhaopeng Tu
Longyue Wang

Subjects

Linguistics

Topics
chinese translation english contextual information machine translation machine translating history experimental context aware

Exploiting cross-sentence context for neural machine translation (2017)

Abstract In translation, considering the document as a whole can help to resolve ambiguities and inconsistencies. In this paper, we propose a cross-sentence context-aware approach and investigate the influence of historical contextual information on the performance of neural machine translation (NMT). First, this history is summarized in a hierarchical way. We then integrate the historical representation into NMT in two strategies: 1) a warm-start of encoder and decoder states, and 2) an auxiliary context source for updating decoder states. Experimental results on a large Chinese-English translation task show that our approach significantly improves upon a strong attention-based NMT system by up to +2.1 BLEU points.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Qun Liu, Andy Way, Zhaopeng Tu, Longyue Wang

Experts in our system

1
Qun Liu
Dublin City University
Total Publications: 31
 
2
Andy Way
Dublin City University
Total Publications: 229
 
3
Zhaopeng Tu
Dublin City University
Total Publications: 6
 
4
Longyue Wang
Dublin City University
Total Publications: 8