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纽马克翻译理论视角下的Neural Machine Translation(节选)英汉翻译实践报告

论文作者:留学生论文论文属性:硕士毕业论文 thesis登出时间:2023-02-05编辑:vicky点击率:557

论文字数:52452论文编号:org202301251259047499语种:英语 English地区:中国价格:$ 66

关键词:英语翻译论文题目范文

摘要:本文是一篇英语翻译论文题目,本报告以神经机器翻译(第8章和第9章)的英译为基础,以纽马克的文本类型学理论以及语义翻译和交际翻译为指导,分析了其中的难点,并针对词汇、句法和文本翻译提出了相应的策略和方法。=

本文是一篇英语翻译论文题目,作者提出了进一步改进本报告的一些建议。首先,应深入学习NMT领域,并对平行文本的翻译进行更全面的比较研究,以更好地翻译这一高度专业的EST文本。此外,这些案例的最终翻译和分析必须交给其他翻译人员和相关领域的专家进一步润色。此外,迫切需要作者具备更扎实的双语能力、更好的调查和验证技能以及更敏锐的批判性思维能力,从而客观分析案例并合理撰写报告。

Chapter One Introduction

1.1Background of the Translation Practic

In July 2017, the Development Plan for a New Generation of Artificial Intelligence, issued by the State Council, made specific arrangements for the development of AI in China (Zhou, 2018:1). In 2020, the Annual Conference of China’s Artificial Intelligence Industry (CCAI), held in Suzhou, released China’s Artificial Intelligence Development Report 2020, pointing out that a new generation of AI is booming worldwide, among which Natural Language Processing (NLP) is one of the core technologies of AI in the past and the next decade. Additionally, Machine Translation (MT) has been the key research direction of NLP, in line with the application goal of AI, which is to let machines help humans to complete tasks that can only be done by humans themselves.

Nowadays, with the vigorous development of overseas travel, foreign language education and international cooperation driven by economic globalization, people’s demand for translation, especially machine translation, has been growing unprecedentedly. Emerging in the 1950s, MT has evolved into the currently popular Neural Machine Translation (NMT) through more than 70 years’ tortuous development (Hutchins & Somers, 1992: 38-40). Characterized by a single structure design and simple translation process, NMT has become the mainstream research method of MT as well as the core technology of commercial online MT systems such as Google and Baidu (Wu, Schuster, et al., 2016: 252-261). 

The intertranslation of Chinese and Western scientific classics will promote mutual exchanges in Science and technology (S&T). The enhancement of NMT implies the successful combination of AI and the translation industry, representing China’s progress in S&T (Guo, et al., 2021: 97-104). The E-C translation practice of Neural Machine Translation (NMT) will help Chinese researchers learn from Western scientific achievements to address today’s urgent need for translation, drive translators to learn the cutting-edge MT technology to improve translation efficiency and provide a reference for those who translate such kind of scientific texts.

1.2Significance of the Translation Practice

In 2018, the Translators Association of China (TAC) released China’s Language Service Industry Development Report 2018. This report indicated in the past decade, the vigorous advancement of translation technology driven by AI has brought out human-computer interactive translation technology which connects MT and CAT①. Against this background, China’s further study of MT, especially the mainstream NMT from abroad, can improve translation speed and quality, promote the booming development of the translation industry, and facilitate economic, scientific and cultural exchanges between countries. The role of scientific texts in transferring advanced S&T is increasingly prominent, and the technological advancement can drive economic growth. Therefore, EST translation under the economic growth has become a special translation application study (Liu, 2016:164-165).

Based on CNKI, the number of scientific translation study papers by Septemb论文英语论文网提供整理,提供论文代写英语论文代写代写论文代写英语论文代写留学生论文代写英文论文留学生论文代写相关核心关键词搜索。

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