本文是一篇英语论文，本文概述了基于MT+PE的《2021年世界贸易报告》翻译项目（节选），对三种最常见的MT错误类型及其伴随的PE策略进行了案例研究。
Chapter One Task Background
1.1.Background of the“MT+PE”Mode
This section mainly introduces the background of MT,the development of PE,aswell as the“MT+PE”translation mode.
1.1.1 Machine Translation
Machine translation(MT)is the process of translating texts from one languageinto another using software rather than a human translator,at least when the“raw”translation is being produced.In order to recognize,research,and make an effort toresolve the many issues involved in automated translation,MT systems are guided bycutting-edge computational linguistics.The notion of machine translation wasdeveloped in the 1930s by the French scientist G.B.Archovny.MT is a sub-field ofcomputational linguistics.W.W.Aver first proposed the concept of machinetranslation in 1949.The Georgetown-IBM project was introduced on January 7,1954,at IBM’s New York headquarters.The first automated machine translation wasperformed on 60 Russian words by IBM’s Model 701 computer.
There are four separate classifications made for MT:
Rules-based MT(RBMT)is based on systematized grammatical rules that arecombined with common lexicons and,depending on the application,specializeddictionaries.
Example-based MT(EBMT)uses analogy in translation.A collection ofsentences in the original language are given to the translation engine.The system isthen given the equivalent translations in the target language.They serve astranslational examples.
Statistical MT(SMT)models go through a learning process in which a sizablequantity of linguistic data is provided to them to study,mainly at the phrase level,andthen apply while producing translations.
1.2.Task Overview
In this practice,Chapter 2 of the World Trade Report 2021 of the World TradeOrganization(WTO)will be used as the material,and Memsource cloud platform willbe selected to divide the sentence segments of translated materials to realize left-rightcomparison translation.Google machine Translation embedded in the platform will beused to automatically translate source language materials and analyze the errors ofmachine translation in this material.The corresponding strategy of manualpost-translation editing is studied.
Chapter Two Introduction to the ST
2.1 General Introduction to the ST
The source text(ST)of the project is select from the second section in the WorldTrade Report 2021.The annual World Trade Report seeks to advance knowledge oftrade trends,trade policy concerns,and the multilateral trading system.In a worldeconomy that is increasingly vulnerable to natural and man-made shocks,the WorldTrade Report 2021 examines current discussions regarding economic resilience andexplains how the WTO may help to increase economic resilience.
The translation project is based on the“MT+PE”mode of the English-Chinesetranslation of the second section in the World Trade Report 2021.The English text ofChapter two contains 9 992 words and the Chinese text 13 587.
2.2 Characteristics of the ST
Peter Newmark(1981:21)concluded texts into three categories:informativetexts,expressive text and vocative text.Informative text refers to textbooks,papersand articles,etc.with scientific,industrial and economic content.In addition,passives,present tense,present perfect,and literal language are frequently used throughout thetext(Newmark,1988:40).Based on Newmark’s research,the ST in this project can beclassified into informative text.The following three aspects to manifest thecharacteristics of the ST and to prove that the ST selected in the project belongs to theinformative text.
2.2.1 Characteristics at Lexical Level
The function of informative text is to convey information and emphasize theauthenticity and accuracy of the content.The text of financial report selected by theauthor is mainly composed of professional terms.The use of these terms can not onlymake the original text more professional and authoritative,reflect the authenticity ofinformation,but also increase the knowledge rese
