Survey of Common Errors of English to Vietnamese Google Translator in Business Contract

Trần Lê Tâm Linh

doi:10.4236/ojml.2013.32013

Home > Journals > Social Sciences & Humanities > OJML

OJML> Vol.3 No.2, June 2013

Share This Article:

Open Access

Survey of Common Errors of English to Vietnamese Google Translator in Business Contract

Abstract Full-Text HTML

Download as PDF (Size:765KB) PP. 101-107

DOI: 10.4236/ojml.2013.32013 5,130 Downloads 8,170 Views Citations

Author(s) Leave a comment

Trần Lê Tâm Linh

Affiliation(s)

Foreign Language Center, University of Science, Viet Nam National University, Hochiminh City, Vietnam.

ABSTRACT

Machine translation is a prolonged and difficult problem, but it becomes more and more attractive due to its huge benefits for our society. Nowadays, Google Translator (GT) is one of the most common machine translation softwares because of its relatively high accuracy. However, some language pairs with their different typology and some specialized texts which are translated by GT have not issued really good translation results yet. In this paper, we survey the common errors of machine translation from the point of view of comparative linguistics in business contracts when these legal documents are translated from English into Vietnamse by using GT. Hopefully, these results can be used to intend the effective ways improving translation models of computer in the future.

KEYWORDS

Machine Translation (MT); Lexical Error; Semantic Error; Word Order Error; Missing Error; Redundant Errors; Google Translator

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Linh, T. (2013) Survey of Common Errors of English to Vietnamese Google Translator in Business Contract. Open Journal of Modern Linguistics, 3, 101-107. doi: 10.4236/ojml.2013.32013.

References

[1]	David, V., Jia, X., Luis, F. D., & Hermann, N. (2006). Error analysis of statistical machine translation output. www.lrec-conf.org/proceedings/lrec2006/pdf/413_pdf.pdf

[2]	Duong, T. N. (2008). Thu tìm hieu do dài cua cau tieng Anh chuyên ngành Luat (A preliminary study of the length of sentence in legal English). DHQGHN, NN 24: 207-215. http://tapchi.vnu.edu.vn/4_208_NN/2.pdf

[3]	Maja, P., & Hermann, N. (2006). Morpho-syntactic information for automatic error analysis of statistical machine translation output. Proceedings of the workshop on statistical machine translation, New York City, June 2006, c2006 Association for Computational Linguistics, 1-6.

[4]	Maja, P., & Hermann, N. (2007). Word error rates: Decomposition over POS classes and applications for error analysis. Proceedings of the second workshop on statistical machine translation, Prague, June 2007, c 2007 Association for Computational Linguistics, 48-55.

[5]	Mary, A. F. (1996). Error classification for MT evaluation. CompuServe 1000 Massachusetts Ave. Cambridge. www.mt-archive.info/AMTA-1994-Flanagan.pdf

[6]	Nguyen Ngoc Hung (2010). Ky thuat soan thao van ban quy pham pháp luat, ngon ngu pháp ly (Editing techniques of law normative act and legal languages). TaiLieu.VN: June 15, 2010. http://www.tech24.vn/.../6025-Ky-thuat-soan-thao-van-ban-quy-pham-pha…

[7]	Sara, S. (2011). Blast: A tool for error analysis of machine translation output. Linkoping: Department of Computer and Information Science, Linkoping University. http://www.aclweb.org/anthology-new/P/P11/P11-4010.pdf