A Statistical Method for Translation Quality Assessment

Shouyi Fan
Foreign Affairs College, Beijing

Abstract

This paper attempts to introduce a new statistical method for making a quantitative assessment of the quality of a translation. A set of criteria was defined, against which the quality of a given unit of translation can be measured. These criteria provide a framework within which a mathematical model is constructed. It takes the fuzzy subset theory as its theoretical basis, trying to solve the problem of translation quality assessment by an approach which might be called analysis-synthesis fuzzy evaluation. Mathematical operations can be performed with the aid of a computer program to yield a grade of membership which indicates the quality of a given translation. The model proposed in this paper is, therefore, of methodological significance.

Table of contents

Up until now, translation quality assessment has remained qualitative rather than quantitative. Following this approach, what we do is give a [ p. 44 ]description of the quality of a work of translation in impressionistic terms in relation to certain standards. Expressions like Excellent, Good, Fair, and Poor are thus often used to indicate the quality of a translation. But these words are vague. An Excellent may not be that excellent, and a Poor may not be all that poor. These terms express values that are felt to be somewhat fuzzy. Therefore, quality of translation is usually considered to be something that cannot be assessed in a crisp manner. However, the fuzzy set theory as first advanced by Lotfi A. Zadeh in 1965 offers us a mathematical means with which translation quality assessment can be subjected to quantitative analysis.

Full-text access is restricted to subscribers. Log in to obtain additional credentials. For subscription information see Subscription & Price. Direct PDF access to this article can be purchased through our e-platform.

References

Dubois, Didier Henri Prade
1980Fuzzy Sets and Systems: Theory and Applica-tions. New York: Academic Press.Google Scholar
Fan, Shouyi
1987 "Fuzzy Set Theory and Evaluation of Translation". China Trans-lators' Journal 4. 1–9.Google Scholar
Kaufmann, Arnold
1975Introduction to the Theory of Fuzzy Subsets, I. New York: Academic Press.Google Scholar
Lakoff, L. George
1972 "A Study in Meaning Criteria and the Logic of Fuzzy Con-cepts". Proceedings of 8th Regional Meeting of Chicago Linguistic Society. University of Chicago 1972 183–227.Google Scholar
Leung, Kam-Tim and Doris Lai-Cheu Chen
1967Elementary Set Theory. Oxford: Oxford University Press.Google Scholar
Miao, Dong-Sheng
1987Introduction to Fuzziology. Beijing: Chinese People's Univer-sity Press.Google Scholar
Nida, Eugene A.
1964Toward a Science of Translating. Leiden: E.J. Brill. Google Scholar
Nida, Eugene A. and Charles R. Taber
1974The Theory and Practice of Translation. Leiden: E.J. Brill. Google Scholar
Nida, Eugene A. and Jan de Waard
1986From One Language to Another: Functional Equivalence in Bible Translation. Nelson.Google Scholar
[ p. 67 ]
Phillips, John L.Jr.
1981Piaget's Theory: A Primer. San Francisco: W.H. Freeman and Company. Google Scholar
Shannon, Claude E. and Warren Weaver
1962The Mathematical Theory of Communication. Urbana: The University of Illinois Press.Google Scholar
Zadeh, Lotfi A.
1965 "Fuzzy Sets". Information and Control 8. 338–353.   CrossrefGoogle Scholar
1972 "A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges". Journal of Cybernetics 2. 4–34.   CrossrefGoogle Scholar
1975a "The Concept of a Linguistic Variable and Its Application to Approximate Reasoning—I". Information Sciences 8.Google Scholar
1975b "Calculus of Fuzzy Restrictions". L.A. Zadeh et al., eds. Fuzzy Sets and Their Applications to Cognitive and Decision Processes. New York: Academic Press, Inc. 1975.   CrossrefGoogle Scholar