Distance-based Reordering in English to Hindi Statistical Machine Translation
|
10.5120/15750-4693 |
Sudhakar Kumawat and Nitish Chandra. Article: Distance-based Reordering in English to Hindi Statistical Machine Translation. International Journal of Computer Applications 89(20):37-40, March 2014. Full text available. BibTeX
@article{key:article,
author = {Sudhakar Kumawat and Nitish Chandra},
title = {Article: Distance-based Reordering in English to Hindi Statistical Machine Translation},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {89},
number = {20},
pages = {37-40},
month = {March},
note = {Full text available}
}
Abstract
This paper compares different reordering models on English to Hindi statistical machine translation system. The two Indo-European languages differ significantly in their word order preferences. While English follows SVO model, Hindi follows SOV model. Therefore both long distance and short distance reordering becomes important. The reordering models available in MOSES SMT are discussed and compared with a more novel approach called distance-based reordering. This new approach significantly improves the quality of English to Hindi translation, both in terms of BLEU score and subjective human evaluation. .
References
- Bharati, Akshar, Vineet Chaitanya, and Rajeev Sangal. Natural Language Processing, a Paninian Perspective. Prentice Hall of India, 1995.
- Bojar, Ond, Pavel Stra, and Daniel Zeman. English-Hindi translation in 21 days. In Proceedings of the 6th International Conference on Natural Language Processing (ICON-2008) NLP Tools Contest, 2008.
- Bushra Jawaid, Daniel Zeman. Word-Order Issues in English-to-Urdu . PBML april 2011. http://ufal. mff. cuni. cz/~jawaid/publications/art-jawaid-zeman. pdf
- Nakul Sharma, P Bhatia, V Singh. English to Hindi Statistical Machine Translation System. Thapar University. 2011
- Koehn, Philipp. Statistical Machine Translation. Cambridge University Press, Cambridge, UK, 2010.
- Michel Galley, Christopher D. Manning. A Simple and Effective Hierarchical Phrase Reordering Model. Proceedings of the 2008 Conference Empirical Methods in Natural Language Processing . Honolulu, October 2008.
- Wang Ling, Joao Grac¸a, David Martins de Matos, Isabel Trancoso, Alan Black. Discriminative Phrase-based Lexicalized Reordering Models using weighted Reordering Graphs. Carnegie Mellon University, Pittsburgh, PA, USA.
- Jurafsky, Daniel and James H. Martin. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Prentice-Hall, Upper Saddle River, NJ, 2000. ISBN 0-13-095069-6.
- Kneser, Reinhard and Hermann Ney. Improved backing-off for m-gram language modeling. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Los Alamitos, California, USA, 1995. IEEE Computer Society Press.
- Yizhao Ni, Distance phrase reordering for MOSES. Pattern Analysis and Intelligent Systems Research Group. Department of Engineering Mathematics University of Bristol
- Chen, Stanley F. and Joshua Goodman. An empirical study of smoothing techniques for language modeling. In Technical report TR-10-98, Computer Science Group, Harvard, MA, USA, August 1998. Harvard University. URL http://research. microsoft. com/en-us/um/people/joshuago/tr-10-98. pdf.
- MOSES , GIZA ++,BLEU tool http://statmt. org/.