本科生毕业论文（设计）册
学院 XXX学院
专业机译
班级 XXXX级机译班
学生 XX
指导教师 XXX
XXXX大学本科毕业论文（设计）任务书
编号：
论文（设计）题目：机器翻译的利与弊
学院： XXX学院专业：机译班级： XXXX机译班
学生姓名： XX 学号： XXXX 指导教师： XXX 职称：副教授
1、论文（设计）研究目标及主要任务
本论文的研究目标是了解机器翻译的发展历程，并通过人工翻译与机器翻译的比较，探讨机器翻译的利与弊。其主要任务是正确地评价机器翻译，合理地使用机器翻译来辅助人工翻译。
2、论文（设计）的主要内容
本论文分为四章，第一章介绍机器翻译在国内外的发展历史，第二章介绍机器翻译的优势，第三章介绍机器翻译的弊端，最后一章讨论了机器翻译的发展前景。
3、论文（设计）的基础条件及研究路线
本论文的基础条件是不同的翻译家及计算机语言学家对机器翻译的研究成果。研究路线是通过具体实例对机器翻译和人工翻译进行多方面的比较, 总结出机器翻译的优势与发展瓶颈。
4、主要参考文献
Brown-Samuelsson, Geoffrey. 2004. A Practical Guide for Translators. Britain: Cromwell Press Ltd.
Hutchins, W. J. & Somer s. 1992. An Introduction to Machine Translation. London: Academic Press .
韩建国. 1999. 浅谈机器翻译问题. 中国科技翻译（2），33.
张景丰. 2009. 机器翻译之利与弊. 河南机电高等专科学校学报(5), 56.
张景丰. 2008. 机器翻译和人工翻译之比较. 新乡学院学报(4), 110.
指导教师：年月日
教研室主任：年月日
XXXX大学本科生毕业论文（设计）开题报告书
XXXX大学本科生毕业论文（设计）评议书
XXXX大学本科生毕业论文（设计）文献综述
本科生毕业论文设计题目机器翻译的利与弊
作者姓名 XX
指导教师 XXX
所在学院 XXX学院
专业（系）机译
班级（届） XXX级机译班
完成日期 XXX 年 4 月 21 日
The Advantages and Disadvantages of Machine Translation
BY
XX
Prof. XXXX, Tutor
A Thesis Submitted to Department of English
Language and Literature in Partial
Fulfillment of the
Requirements for the Degree of B.A in English
At XXXX University
April 21st, XXXX
摘要
机器翻译自从其诞生以来经历了漫长而又曲折的历程，分为四个阶段：开创期，受挫期，恢复期和新时期。它速度快、效率高，彻底改变了传统的手工翻译方式。机器翻译具有很多优势，得到了很多国家的关注，这也因此促进了机器翻译的发展。另一方面，机器翻译仍然面临着许多瓶颈需要攻克。然而，不可否认的是机器翻译已经取得了长足的进展，无论是在技术还是在应用方面，机器翻译都具有广阔的发展前景。
本文首先阐述了机器翻译在国内外的发展历程, 然后介绍了机器翻译的优势及各种应用。并通过具体实例对机器翻译和人工翻译进行比较, 总结出机器翻译存在的弊端,如机器翻译缺少可读性和流畅性，在处理多义词，句子结构，自动分词，语言和文化语境方面能力不足。最后本文预测了机器翻译未来的发展前景。
关键词机器翻译利与弊歧义
Abstract
Since its emergence machine translation has embarked on a winding and long path of development, which can be divided into the following 4 stages: pioneering period, frustration period, recovery period and the new period. Featuring fast speed and high efficiency, machine translation has revolutionized traditional manual translation. Impressed by its vast advantages, machine translation has drawn attention from many countries, which has consequently facilitated its development. On the other hand, machine translation is still confronted with various bottlenecks to tackle. However, it is undeniable that machine translation has achieved tremendous progress and it has a broad future in terms of technologies and applications.
This paper firstly elaborates the development history of machine translation both in foreign countries and China. Then it describes the advantages of machine translation as well as its diverse applications. After comparison between human translation and machine translation through specific examples, it summarizes the disadvantages of machine translation, for example, machine translation lacks readability and fluency and has difficulties in dealing with polysemy, syntactic structure, automatic word segmentation, linguistic and cultural context. Finally, this paper draws a conclusion and predicts the prospect on the research of machine translation.
Key words machine translation advantages and disadvantages ambiguity
Table of Contents
Introduction (1)
Chapter One The evolution of machine translation since its emergence (3)
1.1 Development of machine translation in foreign countries (3)
1.1.1 Pioneering period（1946-1964） (3)
1.1.2 Frustration period（1964-1975） (3)
1.1.3 Recovery period（1975-1989） (4)
1.1.4 New period (1990—now) (4)
1.2 Development of machine translation in China (5)
Chapter Two Advantages of machine translation (6)
2.1 Strengths of machine translation (6)
2.2 Various application of machine translation (7)
2.2.1 Information distribution (7)
2.2.2 Information assimilation (7)
2.2.3 Information exchange (8)
2.2.4 Information access (8)
2.3 Suitable source materials (8)
Chapter Three Disadvantages of machine translation (10)
3.1 Lack of readability and fluency (10)
3.2 Ambiguity (11)
3.2.1 Polysemy (12)
3.2.2 Part of speech (12)
3.2.3 Syntactic ambiguity (13)
3.2.4 Automatic word segmentation (14)
3.2.5 Dictionary volume (15)
3.3 Difficulties in understanding figures of speech (15)
3.4 Context analysis (16)
3.4.1 Linguistic context (17)
3.4.2 Cultural context (18)
Chapter Four Development prospect of machine translation (20)
4.1 Technologies (20)
4.2 Applications (20)
Conclusion (22)
Bibliography (23)
Introduction
Machine translation, or MT for short, is the process of using machine to translate a language into another one. It is an interdisciplinary field of linguistics, natural language processing, artificial intelligence and so on. The ultimate goal of machine translation is to achieve fully automatic translation of natural language.
The notion of using digital computers to translate documents was first put forward by Warren Weaver in 1949. From then on, machine translation had embarked on a long and devious road. At the very beginning, people were excessively optimistic about machine translation. They predicted that imminent breakthroughs of fully automatic systems would come soon. However their enthusiasm was dampened as more and more complicate linguistic problems became more apparent. For example, first, not all the words in one language have equivalent words in another one; Second, many words are poly-semantic and sometimes a sentence may have at least two meanings in a language but computer is not able to decide the exact meaning in the source text. Third, the ways of how sentences are put together are not the same in different languages. These above mentioned challenges are only the tip of the iceberg. In addition, the disappointing translation results of early translation systems frustrated people’s efforts in machine translation research. Researchers began to question the possibility of full automation and good quality However, the spectacular advancements of computer technologies and computational linguistics bring machine translation to life again. These advancements include increased processing speed, enlarged computer memory and improved database technology etc.Besides, there is a strong connection between machine translation and the modern society. For example, when exporters market their products in a foreign country they definitely need documents in the language of that https://www.doczj.com/doc/ca4328144.html,ernments and all kinds of organizations are in great need of faster and cheaper translations. Spurred by all these factors, the passion of researchers was ignited again. As a result, many useful MT systems came into being one after another and are widely used to aid humans in translating various materials about science, industry, journalism etc. And, most significantly, compared to human translation, the machine translation systems featuring low cost and rapid response are able to increase the volume of immediate translations manifold, addressing the social need of quick translation of materials in a foreign language. What’s more, the emergence of the Internet brings about an increasing demand of timely translation online, which is insurmountable to human translators.
Generally speaking, machine translation is used in two ways. One is the need of accurate translation, especially the translation of materials like news, laws, advertisings, product specifications etc. Here machine provides humans with a draft translation to be refined, thus saving a lot of time which would otherwise be wasted in consulting dictionaries. The other is the need of quick translation results which may be grammatically imperfect and lexically awkward but convey the main idea of the source text.
Despite the tremendous improvement of machine translation since its emergence, there is still a long way to go before achieving the final goal of fully automatic translation. Machine translation is still confronted with a lot of technological bottlenecks which haven’t been tackled yet. The application of machine translation is restricted for it can’t be used to translate literary works, laws etc. The translation of machine translation usually is unreadable and grammatically wrong. The processing unit of machine translation is within sentence, so it is not able to analyze the relations between neighboring sentences or paragraphs. Furthermore, machine translation lacks the ability to analyze the context. As is well known, context plays an important role during translation. The meanings of words or sentences depend heavily on context, so the deficiency to analyze it will easily lead to mistranslation.
American inventor Ray Kurzweil once predicted that by 2029 the quality of machine translation would reach the level of human translation. This prediction has triggered heated controversy in the academic community. Anyway, the current development trend of machine translation is favorable. It is believed that machine translation has promising prospects in the future. As long as linguists, computer experts, mathematicians etc work collectively, all the bottlenecks facing machine translation will be solved.
This paper will try to give the readers a coherent picture of many aspects of machine translation, mainly its advantages and disadvantages.
Chapter One The evolution of machine translation since its emergence
1.1 Development of machine translation in foreign countries
Machine translation dates back to as early as 17th century. In the early of this century, RenéDescartes put forward an innovative idea of a universal language in which equivalent meanings of different languages can be expressed in the same way. Then in 1940’s, British engineer Andrew Booth and American scientist Warren Weaver jointly proposed to use computers to translate natural languages for the first time. Strictly speaking, the concept of machine translation was officially put forward in Warren Weaver’s Memorandum on Translation in 1949, which stimulated the research of MT in US. Henceforth, MT embarked on a winding and long path of development, which can be divided into the following 4 periods.
1.1.1 Pioneering period（1946-1964）
In 1954, Georgetown University and IBM of US collectively succeeded in inventing the first Russian-English translation system in the world. This landmark system not only demonstrated the possibility of MT but also kicked off the research of MT.
From 1950s to the first half of 1960s, the two superpowers of US and USSR, impressed by the initial success of MT, invested heavily in MT projects for military, politic and economic purposes. Besides, due to geopolitics and economic needs, many European countries also attached considerable importance to MT. Though at the initial stage, machine translation thrived rather fast around the world.
1.1.2 Frustration period（1964-1975）
For some time optimism was high and machine translation research continued vigorously. Some people predicted that breakthroughs of machine translation technologies and the fully automatic translation systems will come within years.Nevertheless, as people knew more of the complicate linguistics, they were badly discouraged by those seemingly insuperable linguistic problems
In 1964, to have a better evaluation of machine translation research, American Academy of
Science set up Automatic Language Processing Advisory Committee (ALPAC) and started a two-year analysis and test. In October 1966 ALPAC published a report entitled Language and Machine, or ALPAC report for short, which asserted that “machine translation was slower, less accurate and t wice as expensive as human translation and that “there is no immediate or predictable prospect of useful machine translation” (ALP AC, 1966). This report was a head-on blow to the thriving machine translation for it denied the feasibility of machine translation and suggested no further investment in machine translation projects. Consequently the developments of MT run into a dilemma.
1.1.3 Recovery period（1975-1989）
In 1970s, due to the advancement of science and technology as well as the increasing exchange of scientific and technological information among nations, linguistic barrier became more serious. However, the traditional manual translation co uldn’t meet the increasing needs, thus computer was urgently needed to aid in translation. At the same time, the development of computer science and linguistic research, especially the significant advancement of computer hardware technology as well as the application of artificial intelligence in natural language processing, facilitated the recovery of machine translation in terms of technology.
Machine translation projects revived again and then all kinds of translation system came into being one after another, for example, Weinder system, EURPOTRA--a translation system of multiple languages and AUM-METEO system etc.
1.1.4 New period (1990—now)
With wide application of the Internet, integration of world economy and increasing exchange in international community, traditional translation is far from satisfactory. People were unprecedentedly in need of machine translation, which brought a new development opportunity to machine translation.
One of the fastest growing areas of use is in government and all kinds of organizations which are in great need of technical documentation.
Another accelerated application of machine translation is in software localization. Here MT systems are applied to translate materials into other languages of those countries where their softwares are going to be launched.
Besides, driven by the demands of market, commercial translation system comes into operational use and attracts more and more customers.
1.2 Development of machine translation in China
Research of machine translation in China has been highly valued by Chinese government since the initial stage. In 1956, MT was included in the Outline of National Scientific and Technological Development, and later was included in such major research programs as The Sixth Five-Year Plan, The Seventh Five-Year Plan and 863 Program.
In 1957, Institute of language and Institute of Computing Technology in Chinese Academy of Sciences collaborated on a Russian-Chinese translation system and translated nine kinds of different complicated sentences.
During the Cultural Revolution, machine translation experienced a ten-year standstill, but came to life again in the mid 1970s.
From mid 1980s to early 1990s, there appeared two epoch-making translation systems-- KY-1 and MT/EC 863, which indicated the significant progress made in China’s machine translation research.
From early 1990s to now, China has witnessed unprecedented achievement in machine translation and launched various translation systems such as Transtar, Yaxin, Tongyi etc.
Chapter Two Advantages of machine translation
2.1 Strengths of machine translation
Sometimes a translator would be required to finish a work within an unrealistically limited time. The only feasible way in the traditional translation may require a team of translators coordinated by a skillful project manager to work concurrently. The alternative solution is to turn to the machine translation software for help. The speed of machine translation can reach 30,000 or even more characters an hour, five to six times faster than humans. Take translation between English and Chinese for example. A professional translator can translate 200 to 500 characters an hour, while machine translation system can finish the same work within several seconds with an accuracy rate as high as about 80%. Evidently, machine translation accelerates the efficiency of translation significantly, saves a lot of time used for consulting dictionaries, and thus reduces the cost of translation.
Some machine translation softwares have open database to which users can edit or add commonly used jargons. At first it may take some time to enlarge the vocabulary but saves more time in the long term. What’s more, some softwares can also upgrade themselves automatically and expand the vocabulary timely.
Geoffrey Samuelsson-Brown, a technical Swedish translator has illustrated six major advantages of machine translation in his book A Practical Guide for Translators:
●Repetitive or similar texts need to be translated once.
●Once glossaries have been entered in the system, future translation will always be
consistent providing the translator selects the option offered by the terminology management system.
●Greater speed of draft translation, thereby allowing more time for quality control.
● A computer can work on draft translation at any time of the day, thus a 10,000 word
translation that may take a human translator a week to produce could be done overnight ready for editing the next morning.
●Reduction in production costs, thereby producing greater profitability.
●Better quality control since text already entered in the software will not need to be
re-checked if it can be identified uniquely.(Brown-Samuelsson, 2004:77)
2.2 Various application of machine translation
Judging from the quality of current machine translation, there is still a long way to go before realizing the goal of full-automation and good translation quality. But these machine translation systems are already able to meet people’s diverse needs of translation and are widely used in different fields.
From the type of application, machine translation systems fall into the following 4 types: 2.2.1 Information distribution
This kind of system is mainly used by information distributors to translate such materials as news, laws, advertisings, product specifications etc. This type of users needs to have information exactly translated into another language, so they require a very high rate of accuracy. To achieve high accuracy, machine translation generally adopts two ways. One is to use restricted language. In the highly restricted field, machine translation can attain quite satisfactory translation quality. The most typical example is the Canadian TAUM-METEO translation system exclusively used in weather forecast. Some companies also use restricted language in their product specifications, which not only ensures that the information contained is clear and easy to understand but also makes machine translation easier. The second way is machine-aided human translation. One example in point is translation workbench, a computer aided translation system that adopts the technology of translation memory. Besides translation memory, this kind of product also has the functions of management of terminology database, processing of corpus, management of translation projects and so on. At present, this product has developed into a large industrial scale and is well received by professional translators. The most typical example of this product is Trados system, which has more than 40,000 users and secures 70% of translation software market.
2.2.2 Information assimilation
This kind of system serves those who only need to know the general idea but not the exact meaning of the information. This system, which starts developing after the application of the Internet, has attracted a lot of users for it enables a person to understand the basic meaning of websites in foreign languages. One famous example of this is the website of WorldLingo.
2.2.3 Information exchange
This kind of system targets those who need translation service in one-to-one communication. It includes spoken language translation system and text translation system. The former one, spoken language translation system, has made some progress but because of the restrictions of voice technology it’s only used in restricted fields, such as restaurant reservation, customer services etc.The latter one, text language translation system, is free from the problems of voice recognition and is applied in wider areas, such as tourism translation, e-mail translation, online chat translation etc.
This system has the following characteristics: the material to be translated is mainly spoken language but not written language; it is used for specific areas; it needs higher real-time; the interaction between machine and huma n is more complicated…
2.2.4 Information access
This kind of system refers to the embedded machine translation system used for information search, information extraction, text summarization and operation of database etc. Due to the rapid development of the Internet, this type of system is also developing very fast. For example, cross-language information search now has become a major subject in the field of information search.
Among the above mentioned systems, some are quite mature like the computer aided translation systems; some are still at the experiment stage. However, with the improvement of machine translation technologies and better translation quality, more and more machine translation systems will come into application.
2.3 Suitable source materials
Because of the characteristics of machine translation, it is most suitable to translate materials concerning technologies and professional literature. The biggest problem that confronts machine translation is the translation of literary works. Literary translation should produce in the target reader the same emotional and psychological reaction produced in the original source language reader. Strictly speaking, no matter how professional a human translator is, he will find it demanding to achieve equivalence of function and figure of speech, let alone machine translation. It is because that literary works, especially poem, novel, drama and film script, not only convey
浅析语料库对于翻译研究的意义 【摘要】基于语料库的翻译研究在当今已进入一个全新模式，多种语料库被开发应用在人工翻译和机器翻译等实践领域当中。本文对语料库的概念以及某些种类语料库在翻译活动中具体实用情况做出分析，揭示语料库对于翻译研究的意义。 【关键词】语料库；翻译；双语语料库；平行/对应语料库 An Analysis on the Significance of Corpus to Translating Research CHEN Dan （Eastern Liaoning University，Dandong Liaoning 118000，China） 【Abstract】Translating research based on corpus has stepped into a new mode today，and many kinds of corpora are developed and applied in practical fields of manual translation and machine translation. The thesis analyzes the concept corpus and the application of some corpora in translating，which exemplify the significance of corpus to translating research. 【Key words】Corpus；Translating；bilingual corpus；Parallel corpus “语料库”的英语单词corpus来源于拉丁语，意思是body，有“全集”的含义，即“语料的集合”。有的学者认为语料库是基于形式和目的的存储于电子数据库中的文本集合，是描述自然发生语言的集合；也有人认为它是按照明确的语言学标准选择并排序的语言运用材料的汇集，旨在用作语言的样本。国内语料库学者杨惠中对语料库的定义做了较为详细的界定。他指出，“语料库是指按照一定的语言学原则，运用随机抽样方法，收集自然出现的连续的语言运用文本或话语片段而建成的具有一定容量的大型电子文库”。 语料库所收集的语料是真实、自然的语言。不同于普通的文本数据库，它的设计和建设是以系统的理论语言学原则为依据，并且具有明确的目的性。语料库的结构严格依照既定程序设定，以一定研究目的为基础，按学科或语篇类型分类存储。语料库中的语料必须符合科学的语言研究，语料可以随机抽取或按统计学方法采集。 语料库的类型和分类标准很多。按用途分，语料库可分为通用语料库（general corpus）和专用语料库（specialized corpus）；按语料选取时间，语料库可分为历时语料库（diachronic corpus）和共时语料库（synchronic corpus）；按不同结构，语料库可分为平衡语料库（balanced corpus）和自然随机结构语料库（random structure corpus）；按语料库的性质，语料库可分为原始语料库（raw corpus）和标注语料库（annotated corpus）；按语言种类，语料库可分为单语语料库
机器翻译研究现状与展望1 戴新宇，尹存燕，陈家骏，郑国梁 （南京大学计算机软件新技术国家重点实验室，南京 210093） （南京大学计算机科学与技术系，南京 210093） 摘要：本文回顾机器翻译研究的历史，介绍典型的机器翻译方法，包括：基于规则、基于统计以及基于实例的机器翻译方法；针对机器翻译的研究现状，详细介绍和分析了基于混合策略的机器翻译方法，对统计以及机器学习方法在机器翻译中的应用进行了描述；论文还介绍了当前机器翻译评测技术；最后对机器翻译进行总结和展望。 关键字：机器翻译，基于规则，基于统计，基于实例，混合策略，机器学习 Machine Translation:Past,Present,future Dai Xinyu, Yin Cunyan, Chen Jiajun and Zheng Guoliang (State Key Laboratory for Novel Software Technology, Department of Computer Science & Technology Nanjing University, Nanjing 210093) Abstract：This paper firstly presents the history of machine translation, and introduces some classical paradigms of machine translation: RBMT, SBMT and EBMT. Secondly, we introduce the recent research on machine translation, and describe the hybrid strategies on machine translation in detail, and discuss the applications of machine learning for machine translation. We also analyze the current techniques about evaluation on machine translation. Finally, we draw a conclusion and prospect on the research of machine translation. Keywords：Machine Translation, RBMT, SBMT,EBMT, HSBMT, Machine Learning. 1本论文工作得到863课题资助（编号：2001AA114102, 2002AA117010-04） 戴新宇博士生，主要研究自然语言处理；尹存燕助教，主要研究自然语言处理；陈家骏教授，博士生导师，主要研究自然语言处理、软件工程；郑国梁教授，博士生导师，主要研究软件工程。
７２ 计算机教育 2005.4 人／才／培／养／与／就／业机器翻译（Ｍａｃｈｉｎｅ Ｔｒａｎｓ－ｌａｔｉｏｎ）是通过计算机来实现不同自然语言之间的翻译。机器翻译是自然语言处理（Ｎａｔｕｒａｌ ＬａｎｇｕａｇｅＰｒｏｃｅｓｓｉｎｇ）的一个分支，机器翻译与计算语言学（ＣｏｍｐｕｔａｔｉｏｎａｌＬｉｎｇｕｉｓｔｉｃｓ）、自然语言理解（Ｎａｔｕｒａｌ Ｌａｎｇｕａｇｅ Ｕｎｄｅｒｓｔａｎｄｉｎｇ）存在着密不可分的关系。机器翻译的研究与发展取决于计算机科学、数学、语言学、人工智能等多学科的发展，因此机器翻译可以说是一个跨学科的综合性系统工程。人类步入２１世纪以来，随着国际互联网（Ｉｎｔｅｒｎｅｔ）的迅猛发展，网络信息急剧膨胀，国际交流日益频繁以及地球村的形成，机器翻译正在逐渐成为克服人们之间进行交流时所面临的语言障碍的重要手段，同时也面临着很大的市场机遇和挑战。 历史的回顾 从美国人维弗（Ｗａｒｒｅｎ?Ｗｅａｖｅｒ）于１９４９年发表《翻译》备忘录并正式提出机器翻译的思想以来，机器翻译已经走过了５０多个风风雨雨的春秋。在这期间，机器翻译可以说经历了一条曲折而漫长的 发展道路。 １９５４年，在美国乔治敦大学（Ｇｅｏｒｇｅｔｏｗｎ Ｕｎｉｖｅｒｓｉｔｙ）进行了 人类历史上的第一次机器翻译的公开演示。尽管演示尚不算很成功，但是它却具有划时代的意义，因为它拉开了人们研究机器翻译 的序幕。 从２０世纪５０年代开始到２０世纪６０年代的前半期，机器翻译的研 究呈不断上升的趋势。美国和前苏联两个超级大国出于军事和政治经济目的，纷纷对机器翻译项目提供了大量的资金支持，而欧洲国家由于地缘政治和经济的需要也对机器翻译研究给予了相当大的重视。 １９６６年，美国科学院发表的ＡＬＰＡＣ报告使当时正在蓬勃发展的机器翻译陷入了停滞的状态。现在来看，该报告是非常片面、狭隘和短视的。 从２０世纪６０年代中后期到整个７０年代，整个机器翻译领域处于一个相对平稳发展的时期，而在某些国家，特别是加拿大和欧盟，机器翻译的研究却取得了比较显著的进步。尤其是在加拿大，由于双语文 化的影响，政府积极支持机器翻译的研发工作，１９７６年，加拿大蒙特利尔大学与加拿大联邦政府翻译局联合开发了提供天气预报服务的实用性机器翻译系统ＴＡＵＭ－ＭＥＴＥＯ，该系统的成功开发标志着 机器翻译已经在某些领域达到了实用化的程度。 进入２０世纪８０年代以来，由于计算机科学、语言学研究的发展，特别是计算机硬件技术的大幅度提高以及人工智能在自然语言处理上的应用，机器翻译在全世界范围内开始复苏，并在随后的９０年代取得了长足的进步。 ２０世纪９０年代以来的机器翻译技术的新进展 １．机器翻译的分类 进入２０世纪９０年代，机器翻译领域的的研究方法基本上可以分为两大类，即基于规则（Ｒｕｌｅ－Ｂａｓｅｄ）和基于语料库（Ｃｏｒｐｕｓ－Ｂａｓｅｄ）的方法。基于规则的方法又可以分为基于转换的方法和基于中间语言的方法，基于语料库的方法又可以分为基于统计的方法和基于实例的方法。传统的基于规则的方法又可以 机器翻译的现状和发展趋势 中国软件与技术服务股份有限公司 岳涛／文 ◆ 课外新知 ◆