Study of Ambiguities of English-Chinese Machine Translation

Juan Juan Suo; Bao Ying Yu; Yue Juan He; Guang Ya Zang

doi:10.4028/www.scientific.net/AMM.157-158.472

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 157-158Study of Ambiguities of English-Chinese Machine...

Study of Ambiguities of English-Chinese Machine Translation

Abstract:

Ambiguities is one of the biggest obstacles of English-Chinese machine translation. In order to make the disambiguation more easily and effectively, the reasons of ambiguities why the quality of machine translation is very low from the perspective of linguistics were analyzed. And then some measures of disambiguation were proposed. This study has significance for the development of English-Chinese machine translation.

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Periodical:

Applied Mechanics and Materials (Volumes 157-158)

Pages:

472-475

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.157-158.472

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Online since:

February 2012

Authors:

Juan Juan Suo, Bao Ying Yu, Yue Juan He, Guang Ya Zang

Keywords:

Machine Translation, Measure, Obstacle, Reason

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References

[1] W. J. Hutchins, H. L. Somers, An Introduction to Machine Translation. London, Academic Press, (1992).

Google Scholar

[2] Jean Francois Mari, Jean Paul Haton, Abdelaziz Kriouile, Automatic word recognition based on second order Hidden Markov Models, IEEE Trans. on Speech and Audio Proc. 5(1997) 22- 25.

DOI: 10.1109/89.554265

Google Scholar

[3] J.M. Ye, Ambiguities and disambiguation in the English-Chinese Machine Translation. Guanxi Normal University. (2002).

Google Scholar

[4] R. Dale, H. Moisl, H. Somers, A Handbook of Natural Language Processing, New York, Marcel Dekker, (2000).

Google Scholar

[5] D. Arnold, L. Balkan, R. L. Humphreys, S. Meijer, L. Sadler, Machine Translation: an Introductory Guide, Oxford: Blackwell, (1994).

Google Scholar

[6] D. McCarthy, R. Navigli, The English lexical substitution task, Language Resources and Evaluation. 43 (2009) 139-159.

DOI: 10.1007/s10579-009-9084-1

Google Scholar

[7] K. Duh, Ranking vs. regression in machine translation evaluation. In Proc. ACL 3rd Workshop on Statistical Machine ranslation, Columbus, USA, (2008).

DOI: 10.3115/1626394.1626425

Google Scholar

[8] C. Callison-Burch, C. Fordyce, P. Koehn, C. Monz, Schroeder, Further meta-evaluation of machine translation. In Proc. CL Third Workshop on Statistical Machine Translation, Columbus, USA, (2008).

DOI: 10.3115/1626394.1626403

Google Scholar

[9] M. Yang, S. Sun, J. Zhu, Improvement of machine translation evaluation by simple linguistically motivated features, Journal of Computer Science and Technology. 26(2011)57-67.

DOI: 10.1007/s11390-011-9415-8

Google Scholar