试述机器翻译构建集成系统：基于规则与统计数据机器翻译

论文导读：ionProcessoftheMind42

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摘要：机器翻译的进展以最早提出论述设想到今天已经经历了六十多年的历史了。如今主流的机器翻译算法主要分成两大阵营：基于规则以及基于统计数据的机器翻译。基于规则的机器翻译核心是依赖于预先人工设置的语法规则模块作为语法浅析的凭据；而对于基于统计数据的机器翻译来说，翻译的核心就是网络爬虫的文件扫描归类机制，以及该机制所创建的动态参考数据库。也就是说，基于规则的机器翻译是模块性系统，而基于统计数据的机器翻译是基于历程类系统。本论文以乔姆斯基语法的视角下阐述基于规则的机器翻译系统独特的模块化处理优势以及在具体自然语言处理上的不足，并以奈达对翻译历程的论述的视角下浅析基于统计数据的机器翻译系统的历程优势以及语法浅析不稳定的劣势。本论文通过结合基于规则的翻译系统的“图书馆”和“语法浅析器”以及基于统计数据的翻译系统的“爬虫”（也称漫游）机制来建立一个集成模块优势和历程优势的系统，通过将图书馆的语法机制融入奈达的翻译步骤来解决基于统计数据翻译系统中的语法浅析不确定性，弥补前者在自然语言处理上的不足以及后者在语法浅析上的薄弱。本论文最后勾勒了机器进展将来以图书馆和语法浅析器为借鉴，以爬虫建立后备资料数据的走势，并在系统和接口硬件上集成的走势以及展望关键词：机器翻译论文人工智能论文基于规则翻译论文基于统计学数据翻译论文爬虫论文
本论文由www.7ctime.com,需要论文可以联系人员哦。摘要4-5
ABSTRACT5-8
Chapter One: Introduction8-11

1.1 Research Background8

1.2 Research Method8-9

1.3 Structure of the Thesis9

1.4 Research Purpose9-11

Chapter Two: A Review of Machine Translation11-19
2.1 Major Events and Theories in the History of Machine Translation11-13

2.2 Current Difficulties13-19

2.1 On Linguistic Layer14-17

2.2.

1.1 On Word Level14-15

2.2.

1.2 On Phrase Level15-16

2.2.

1.3 On Sentence Level16-17

2.2.2 On Programming Layer17
2.2.3 Two Major Camps of Machine Translation17-19
Chapter Three：Towards a Modular Rule-based Machine Translation System from thePerspective of Chomsky Grammar19-30
3.1 Estabpshing Library and Its Components19-26
3.

1.1 Word Dictionaries19-21

3.

1.2 Phrase Dictionaries21-22

3.

1.3 Other Dictionaries22-26

3.

1.3.1 Sentence Dictionaries23-25

3.

1.3.2 Passage Dictionaries25-26

3.2 Parsing26-30
3.

2.1 Expanding XP Rule27-28

3.

2.2 Parsing: Top-Down or Bottom-up?28-30

Chapter Four: Towards a Procedural Statistical Machine Translation System from thePerspective of Nida’s Towards a Science of Translating30-41
4.1 Current Situation of Statistical Machine Translation30-31
4.2 Applying Nida’s Science of Translating31-41
4.2.1 Perusing through the Entire Document32-33
4.2.2 Attaining Extra-pnguistic Information33-34
4.2.3 Evaluating the Merits and Drawbacks of Existing Versions ofTranslation34-36
4.2.4 Sketching a Draft of Each Conceivable Semantic Unit36-37
4.2.5 Reviewing and Revising the Sketch37-38
4.2.6 Pronouncing Text for Literary Features38-39
4.

2.7 Reader Receptivity Feedback39-41

Chapter Five: Constructing an Integrated Modular and Procedural System ofRule-based and Statistical Machine Translation41-51
5.1 Empirici of Statistical Machine Translation versus Classic Grammar ofRule-based Machine Translation41-42
5.2 Towards an Algorithm That Simulates the Cognition Process of the Mind42
5.3 Principles of a论文导读：gualandMultipngualMachineTranslationMapping526.2TheParadoxofIsolatingIntra-pnguisticInformationandExtra-pnguisticInformation52-54Bibpography:54-57Acknowledgements57上一页12
Modular and Procedural System42-46
5.4 Blueprint of an Integrated System: Rule-based and Statistical MachineTranslation46-51
Chapter Six: Concluding Remarks51-54
6.1 Prospect of Machine Translation Development51-52
6.1.1 Integrated Machine Translation with Peripheral Multimedia Support51-52
6.1.2 Interpngual and Multipngual Machine Translation Mapping52
6.2 The Paradox of Isolating Intra-pnguistic Information and Extra-pnguisticInformation52-54
Bibpography:54-57
Acknowledgements57