Translation Of SAM From The Perspective Of NMEV

Metonymy as a basic language phenomenon has attracted enough attention for years no matter being regarded as a speech figure or a way of basic cognition for human beings. Scholars study metonymy from every possible aspect. Translators also find interest in metonymy. Their studies vary from embodiment of metonymy translation in literature to translation mechanism of metonymy to translation strategies of metonymy, Which is fruitful enough.This thesis is going to make use of a newly proposed theory about translation--Pragmatic Markedness Equivalence Principle(PMEP),and develop Numerical(Pragmatic- Markedness) Equivalence Value(NEV) which is used to compare different target texts into a new model-- Numerical PragmaticMetonymic-Markedness Equivalence Value(NMEV) to calculate the markedness value of a source text and a target text, thus to estimate the quality of the target text.NMEV is developed based on NEV. The first difference of the two models lies in that parameters chosen in NEV are temporary while in NMEV, speech act metonymy is regarded as a permanent parameter that will never disappear in the parameter table, which makes the comparison between source text and target text more reasonable and accurate. The second difference lies in that NEV is mainly used to compare two target texts while NMEV can not only be used to compare two and more different target text, it is also suitable for the estimate of one single target text.The working mechanism of NMEV is that we choose five to ten parameters which may include speech act metonymy, address term, wording, rhetoric, structure, implication, presupposition, negation, style, vagueness and printing and so on, and then we give each of the chosen parameter a certain value. The total score is 10 points, and the nearer the markedness value between source text and target text, the more points the target text gets. Any other minor mistakes may lead to a deduction in points. Finally, we add up all the score of the parameters and other compensation value and so on. If the total score is over 90(100 as the full mark), then the target text can beregarded as a good and qualified translation.To prove the feasibility and practicability, this thesis will use rhetorical questions in Thunderstorm written by Cao Yu and translated by Barnes and Wang Zuoliang as a closed corpus. We’ll classify the 253 rhetorical sentences into 5 types and chosen a certain representatives from each type to analyze. The taxonomy is based on Searle’s classification to speech acts, which goes as follows:Through a thorough analysis, we get three conclusions: A) Markedness value of Barnes and Wang Zuoliang’s translation to rhetorical questions of speech act metonymy are equivalent to that of the source text, which makes the translation a good and qualified one. B) Though analyzing, NMEV prove to be feasible and practical, which can be used to estimate any other translation. C) Translation of Speech act metonymy can reflect one’s translation level, which deserve to get more attention.