Journal of Universal Language
Sejong University Language Research Institue
Article

Shift in Controlled English Norms for Different Purposes and for Different Machine Translation Systems

Chung-ling Shih1
1National Kaohsiung First University of Science and Technology

Copyright ⓒ 2016, Sejong University Language Research Institue. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Published Online: Jan 01, 2017

Abstract

This research identifies different controlled English (CE) norms to be followed in technical writing for a variety of purposes and for different machine translation (MT) systems. The results of the investigation show that CE norms for MT application are stricter than those for communicative reading. The primary inference here is that human beings can interpret the meanings of polysemous words, pronouns, prepositional phrases based on the context and easily detect the misspellings, but MT systems fail to do so. In addition, a comparison of CE norms for the application of two MT systems indicates that the corpus-based Google MT is less constrained than rule-based TransWhiz in the lexical area. This phenomenon is attributable to the selection of a highly probabilistic module as the semantic scoring preference for the suggested translation provided by Google MT, not word-for-word translation by TransWhiz. In contrast, Google MT is more constrained than TransWhiz in the syntactic area. The inference is that TransWhiz parses syntactic constructions and transfers the parsing result based on grammatical rules stored in the MT system, so it may modify the original word sequence to make the translation conform to linguistic patterns in the target language. Contrary to this, Google MT depends on fuzzy or exact matches statistically retrieved from the labeled corpus. If no matches can be found, syntactically inappropriate translations will be produced. Seen in this regard, CE norms are never fixed and have to be modified through the evolution of time and MT technology.

Keywords: CE norms; man/reading; machine/translation; diachronic; synchronic; dynamic nature

REFERENCES

1.

Adrianens, G. & L. Macken. 1997. Technological Evolution of a Controlled Language Application: Precision, Recall and Convergence Tests for SECC. In Proceedings of the Sixth International Conference on Theoretical and Methodological Issues in Machine Translation (TMI 95). Leuven, Belgium: Katholieke Universiteit. 123-141.

2.

Allen, J. 2000. Controlled Language -- Changing Faces. International Journal for Language and Documentation (IJLD) 3, 20-21.

3.

Arnold, D., et al. 1993. Machine Translation: An Introductory Guide. London: Blackwells.

4.

Bernth, A. 1999. Controlling Input and Output of MT for Greater Acceptance. In The Proceedings of The 21st ASLIB Conference. London: Aslib Proceedings.

5.

Bernth, A. & C. Gdaniec. 2001. MTranslatability. Machine Translation 59.1, 175-218.

6.

Ceusters, F., et al. 1998. From a Time Standard for Medical Informatics to a Controlled Language for Health. J. Med Inform, 48, 1-3, 85-101.

7.

Gdaniec, C. The Logos Translatability Index in Technology Partnerships for Crossing the Language Barrier. In Proceedings of the First Conference of the Association for Machine Translation in the Americas. Washington, DC: AMTA. 97-105.

8.

Kaji, H. Controlled Languages for Machine Translation: State of the Art. In Proceedings of MT Summit VII. Singapore: Kent Ridge Digital Labs. 3-8.

9.

Laviosa, S. 2002. Corpus-Based Translation Studies, Theory, Findings, Applications. Amsterdam: Editions Rodopi BV.

10.

Lehtola, C. et al. Controlled Language Technology in Multilingual User Interfaces. A paper presented at the 4th ERCIM Workshop on "User Interfaces for All" 19-21 October, 1998, Stockholm, Sweden. Available at URL <http://www.ui4all.gr/UI4ALL- 98/lehtola.pdf> Nov. 25, 2008.

11.

O'Brien, S & J. Roturier, How Portable are Controlled Language Rules? A Comparison of Two Empirical MT Studies, In: Maegaard, Bente ed. Machine Translation Summit XI, 10-14 September 2007, Copenhagen: Centre for Language Technology. 345-352.

12.

Shih, C. 2002. Theory and Application of MT/MAHT Pedagogy. Taipei: The Crane Publishing Co. Ltd.

13.

Shuttleworth, M. & M. Cowie. 1997. Dictionary of Translation Studies. Manchester, UK: St. Jerome Publishing.

14.

Tanaka, H. 1999. What Would We Do Next for MT System Development? In Proceedings of MT Summit VII, 13-17 September 1999, Singapore: Centre for Language Technology. 3-8.

15.

Tedopres International BV. 1974-2007. Simplified Technical English Software and Services. Available at URL <http:// www.simplifiedenglish.net/en/controlled_english/> Nov. 2, 2008.

16.

Toury, G. 1995. Descriptive Translation Studies and Beyond. Amsterdam: John Benjamins.

17.

Underwood, L. & B. Jongejan. 2001. Translatabiltiy Checker: A Tool to Help Decide Whether to Use MT. In Proceedings of MT Summit VIII. Santiago de Compostela, Spain: (No Publisher). 363-368.

18.

Wojcik, H. & E. Hoard. 1996. Controlled Languages in Industry. Available at URL <http://cslu.cse.ogi.edu/HLTsurvey/ch7node8. html> Dec. 2, 2008.