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关于口译员笔记含糊问题的英语翻译学探讨—基于“第三届世界互联网大会大数据论坛”两个模拟会议演讲的中英交替传译案例分析

日期:2018年03月22日 编辑:ad201107111759308692 作者:无忧论文网 点击次数:1678
论文价格:300元/篇 论文编号:lw201803211357498206 论文字数:47247 所属栏目:英语翻译学论文
论文地区:中国 论文语种:English 论文用途:硕士毕业论文 Master Thesis

本文是英语翻译论文,本文的目的是针对消除我在两个演讲上遇到的笔记错误(前演讲也发现了这些错误),并在这样做,我会分析我的笔记,为了检测到整体结构上的“弱点”,包括可以被省略或被更加准确的短词取代的笔记(反映原文的意思)。


CHAPTER ONE: INTRODUCTION


1.1 Research Background

In a globalized world where studying abroad has become a very common thing for theyoung generations of students, China has also been following the global trends bypromoting a very open educational policy, in which students hailing from differentcultural and social backgrounds enjoy the opportunity to follow various programs atprestigious universities. One of these programs is the Master’s Degree of Interpretingand Translation - from English to Chinese. As one can deduce from the name of theprogram, to have English or Chinese as your mother-tongue is essential forovercoming any of the difficulties that may occur in the process of interpretingbetween these two languages. Still, there are more and more self-confident foreignstudents whose mother-tongue is not English, nor Chinese and who choose to followthis Master’s degree, despite the fact that most of them are clearly aware that their nonnativeness in Chinese or English will more or less impede their attempts to enhancetheir interpretation skills, and can also enlarge the gap between them and the nativeChinese and English students and moreover it can undermine their confidence inself-enhancement.

Aware of their “linguistic handicap” and also of the fierce market competition, inwhich the “survival of the fittest” can easily be applied, these foreign students havenot other way to enhance their interpreting skills than that of finding strategies thatwill help them reduce the linguistic gap between them and the native speakers. AChinese proverb states that “the palest ink is greater than the strongest memory(广记不如淡墨).” - on the basis of such a thought had I commenced the writing of mypaper, and from the explanation of this idea am I going to try to make you understandwhy trying to solve your own note-taking problems can ultimately enhance your note-taking skills and furthermore your interpreting skills.

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1.2 The definition of Obscurity

The core problem on which my paper is based, the concept of Obscurity, is defined,according to Oxford Advanced Learner’s Dictionary, as “the quality of being difficultto understand” and that’s why I want to correlate this word to two other relevant terms:incomprehensibility and illegibility. Whilst the incomprehensibility of one’s notesrefers to the fact the person in cause can read its notes but not understand the meaningor the connection with the context, intelligibility refers to the case in which one can’teven read his own notes - when the notes appear like simple drawings. Still, the readermust understand that by obscurity I’m not solely referring to “unbreakable codes”rolled over the pages of my notebook; in some cases these problematic signs, symbolsor abbreviations can be deciphered, however this may consume a few seconds orprobably more, and there is no time to spare in this fierce “linguistic marathon” calledinterpretation. Moreover, there’s also the risk to panic and forget the idea or thecontent. Therefore, the issue in cause can be much more complex than it seems,dividing the central problem of this paper in two types: Partial Obscurity(when signs or the connection between different signs on the paper takes too much time todecipher) and Total Obscurity(when the symbol is simply impossible to decipher,giving free way to deduction); these two names were use in order to make the readerbetter understand the nature of the note-taking mistakes, even though the followingchapters won’t mention them, a more in-dept approach being preferred.

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CHAPTER TWO: CASE STUDYANALYSIS


2.1 Case Description

At the mock conference based on the Big Data Forum on the 3rdWorld InternetConference from 2016, my task was to interpret Deng Maicun’s 7 minutes longintroductory speech on Big Data, and Chen Jinjun’s 8 minutes long speech on BigData - BigApplication.

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