《自然语言处理综论（第2版）》打印版导览：核心技术与应用详解

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《自然语言处理综论（第二版，英文打印版）》是由Daniel Jurafsky和James H. Martin合著的经典之作，该书在自然语言处理和计算语言学领域占有重要地位。这本教材全面深入地探讨了自然语言处理的各种核心概念和技术，旨在帮助读者理解并掌握从基础知识到高级主题的广泛内容。该书共分为四个部分： 1. **Part I：MORPHOLOGY** - 这一部分涵盖了形态学的基础，包括正则表达式与自动机（Chapter 2），词汇与变换器（Chapter 3），n-gram模型（Chapter 4），词类和词性标注（Chapter 5），以及隐马尔可夫模型和最大熵模型（Chapter 6）。这些章节介绍如何分析和处理单词结构，是语言理解的基石。 2. **Part II：PHONETICS** - 关注语音学和语音合成技术（Chapter 7-8），接着是自动语音识别（ASR）的理论和实践，包括基础（Chapter 9）及进阶话题（Chapter 10），以及计算音韵学（Chapter 11）。这部分内容对于声音转文本系统至关重要。 3. **Part III：SYNTAX** - 进入句法层面，涵盖了英语的正式语法（Chapter 12），上下文无关文法解析（Chapter 13），统计解析（Chapter 14），语言复杂性理论（Chapter 15），以及特征和统一性概念（Chapter 16）。这些章节讨论了句子结构的规则和语言模型。 4. **Part IV：SEMANTICS AND PRAGMATICS** - 最后一部分探讨语义和语用学，如意义的表示（Chapter 17）、计算语义学（Chapter 18）、词汇语义（Chapter 19）以及计算机处理语言理解和交流的实际应用。这本书不仅适合研究生和专业人士作为深入学习的参考书籍，也对研究人员和工程师设计和实现自然语言处理系统提供了宝贵资源。通过阅读本书，读者可以建立起坚实的自然语言处理基础，了解不同技术在实际应用中的操作流程，以及如何结合理论与实践进行创新。

DRAFT

14 Chapter 1. Introduction

inventio n of the calculus by Leibnitz and by Newton, the multiple development o f the

theory of natural selection b y Wallace and by Darwin, and the multiple invention of

the telephone by Gray and Bell.

But Merton gives a further array of evidence for the

hypothesis that m ultiple discovery is the rule rather than the exception, including many

cases of putative singletons that turn out be a rediscovery of previously unpublished or

perhaps inaccessible work. An even stronger piece of evidence is his ethnomethodolog-

ical point that scientists themselves act under the assumption that multiple invention is

the norm. Thus many aspects of scientiﬁc life are designed to help scientists avoid be-

ing “scooped”; submission dates on journal articles; careful dates in research records;

circulation of preliminary or technical reports.

1.6.8 A Final Brief Note on Psychology

Many of the chapters in this book include short summaries of psychological research

on human processing. Of course, understanding human language processing is an im-

portant scientiﬁc goal in its own right and is part of the general ﬁeld of cogn itive sci-

ence. However, an understanding of human language processing can often be helpful

in building better machine models of language. This seems contrary to the popular

wisdom, which holds that direct mimicry of n ature’s algorithms is rarely useful in en-

gineering applications. For example, the argument is often made that if we copied

nature exactly, airplanes would ﬂap their wings; yet airplanes with ﬁxed wings are a

more successful engineering solution. But language is not aeronautics. Cribbing from

nature is sometimes useful for aeronautics (after all, airplanes do have wings), bu t it is

particularly useful when we are trying to solve human-centered tasks. Airplane ﬂight

has different goals than bird ﬂight; but the goal of speech recognition systems, for ex-

ample, is to perform exactly the task that human court reporters perform every day:

transcribe spoken dialog. Since people already do this well, we can learn from nature’s

previous solution. Since an important application of speech and language processing

systems is for human-computer interaction, it makes sense to copy a solution that be-

haves the way people are accustomed to.

1.7 SUMMARY

This chapter introduces the ﬁeld of speech and language processing. The following are

some of the highlights of this chapter.

• A good way to understand the concerns of speech and language processing re-

search is to consider what it would take to create an intelligent agent like HAL

from 2001: A Space Odyssey, or build a web-based question answerer, or a ma-

chine translation engine.

• Speech and language technology relies on formal models, or representations, of

Ogburn and Thomas are generally credited with noticing that the prevalence of multiple inventions sug-

gests that the cultural milieu and not individual genius is the deciding causal factor in scientiﬁc discovery . In

an amusing bit of recursion, ho wever, Merton notes that even this idea has been multiply discovered, citing

sources from the 19th century and earlier!

DRAFT

Section 1.7. Summary 15

knowledge of language at the levels of phonology and phonetics, morphology,

syntax, semantics, pragmatics and discourse. A small number of formal models

including state machines, formal rule systems, logic, and probabilistic models

are used to capture this knowledge.

• The foundations of speech and language technology lie in computer science, lin-

guistics, mathematics, electrical engineering and psychology. A small number of

algorithms from standard frameworks are used throughout speech and language

processing,

• The critical connection between language and thought has placed speech and

language processing technology at the center of debate over intelligent machines.

Furthermore, research on how people interact with complex media indicates that

speech and language processing technology will be critical in the development

of future technologies.

• Revolutionary applications of speech and language processing are currently in

use around the world. The creation of the web, as well as signiﬁcant recent

improvements in speech recognition and synthesis, will lead to many more ap-

plications.

BIBLIOGRAPHICAL AND HISTORICAL NOTES

Research in the various subareas of speech and language processing is spread across

a wide number of conference proceedings and journals. The conferences and journals

most centrally concerned with natural language processing and computational linguis-

tics are asso ciated with the Association for Computational L inguistics (ACL), its Eu-

ropean counterpart (EACL), and the International Conference on Computational Lin-

guistics (COLING). The annual proceedings of ACL, NAACL, and EACL, and the

biennial COLING conference are the primary forums for work in this area. Related

conferences include various proceedings of ACL Special Interest Groups (SIGs) such

as the Conference on Natural Language Learning (CoNLL), as well as the conference

on Empirical Methods in Natural Language Processing (EMNLP).

Research on speech recognition, understanding, and synthesis is p resented at the

annual INTERSPEECH conference, which is called the International Conference on

Spoken Language Processing (ICSLP) and the European Conference on Speech Com-

munication and Technology (EUROSPEECH) in alternating years, or the annual IEEE

International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP).

Spoken language dialogue research is presented at these or at workshops like SIGDial.

Journals include ComputationalLinguistics, Natural LanguageEngineering, Speech

Communication, Computer Speech and Language,theIEEE Transactions on Audio,

Speech & Language Processing and the ACM Transactions on Speech and Language

Processing.

Work on language processing from an Artiﬁcial Intelligence perspective can be

found in the annual meetings of the American Association for Artiﬁcial Intelligence

(AAAI), as well as the biennial International Joint Conference on Artiﬁcial Intelli-

DRAFT

Section 1.7. Summary 17

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