Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)

A Hybrid Approach For Spoken Language Machine Translation

Authors
Wenhan Chao1, Zhoujun Li, Yuexin Chen
1School of Computer Science, National University of Defense Technology, Changsha, Hunan, P.R.China
Corresponding Author
Wenhan Chao
Available Online October 2007.
DOI
10.2991/iske.2007.197How to use a DOI?
Keywords
SMT, EBMT, Re-Ordering model
Abstract

In this paper, we propose a hybrid approach, which is a statistical machine translation (SMT), while using an example-based decoder. In this way, it will solve efficiently the re-ordering problem in SMT and the problems for spoken language MT, such as lots of omissions, idioms etc. We present a novel re-ordering model for SMT firstly and then an example-based decoder. Through experiments, we show that this approach obtains significant improvements over the baseline on a Chinese-English spoken language translation task.

Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
Series
Advances in Intelligent Systems Research
Publication Date
October 2007
ISBN
978-90-78677-04-8
ISSN
1951-6851
DOI
10.2991/iske.2007.197How to use a DOI?
Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Wenhan Chao
AU  - Zhoujun Li
AU  - Yuexin Chen
PY  - 2007/10
DA  - 2007/10
TI  - A Hybrid Approach For Spoken Language Machine Translation
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1154
EP  - 1160
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.197
DO  - 10.2991/iske.2007.197
ID  - Chao2007/10
ER  -