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تحليل اسلوبي قائم على لسانيات المدونات اللغوية للخسارة المعجمية في ثلاث ترجمات انكليزية للقران باستخدام نوع الكلمة علامة الكلمة ومؤشر جايرود == A Corpus - Based Stylistic Analysis of Lexical Loss in Three English Quranic Translations Using Type/Token Ratio and Guiraud’s Index
Author name:
عبد الحق عبد الكريم عبد الله السهلاني
Supervisor name:
خالد شاكر حسين
General topic:
Foreign Languages
Specific topic:
English - Applied Linguistics
Degree:
Master
University:
University of Thi-Qar - College Of Education For Human Sciences - Department Of English Language
Language:
English
University location:
Dhi Qar
First pages:
06T1212 - p.pdf
Abstract:
With the aid of corpus linguistics and stylistics in respect to their meeting area corpus stylistics, the researcher measures the lexicons of the three English Quranic translations (those of Yusuf, Pickthall and Muhammad) which have shown different degrees of lexical loss in comparison with the original Arabic Quranic text. These degrees go hand in hand with the size of the linguistic repertoire each translator utilizes in his translation to such an extent that it sounds rather promising to regard lexical loss measure as a trustworthy stylistic marker. That is, each translator has his own distinctive rate of lexical loss that might be an idiosyncratic marker of his translational style.Though loss might not be limited only to one linguistic level (i.e., lexical level) at the expense of other levels, these translations have been characterized by various degrees in terms of the limits of the size of vocabulary each translation holds. However, three hypotheses have been included in this study. First, corpus stylistics is considered to be a reliable source in verifying the validity of controversial issues about lexical loss measurements. Second, the measures of Type/Token Ratio and Guiraud's index can quantify the size of lexical loss efficiently when any translator tries to translate Arabic into English. Thirdly, the lower the degree of lexical loss between the source text and the target text, the more accurate and reliable the translator.After an extensive verification of data reliability, both Arabic and English corpora are segmented into (123) samples. The whole Arabic corpus is distributed into (27) samples. As for the English corpus, it is totally tokenized into (96) samples : Yusufs translation is distributed into (34) samples, Pickthalls translation (31) and Muhammads translation (31). Each sample approximately holds around (5,000) tokens.XIIIAccordingly, the use of Farasa Tools, specifically segmentation module, helps in the morphological analysis of the Arabic corpus. It is so valuable to neutralize the morphological differences between Arabic (a synthetic language) and English (an analytical language). Hence, equalizing the two corpora can be done only by using Farasa tools, a matter that TTR (Type/Token Ratio) and GI (Guirauds Index) analyses can produce more reliable results than what can be produced without working on such tools. Besides, TTR analysis and GI analysis are verified quantitatively and qualitatively. The former is done by using the user - friendly software WordSmith Tools (4.0), specifically Wordlist tool. As for the latter, it is done by using Excel, specifically SQRT equation. To this end, the results taken from such programs are plotted graphically using Microsoft Excel Spreadsheets.The difference, as far as the lexical loss of the entire target texts is concerned, gives an actual indication of where lexical losses do occur among the three translations in comparison with their original Quranic text. Finally, an assessment of the most accurate and reliable English translation of the Glorious Quran can be attained depending on the difference between the size of the Arabic Quranic lexicon and those of the target texts. It is therefore found that : Yusuf's translation ranked in the first place due to the least degree of lexical loss it showed - this makes it relatively the most accurate and reliable translation to the Glorious Qur'an; Pickthall's centered in the second place in terms of lexical loss followed by Muhammad's, in the third place, which revealed the highest degree of lexical loss.
