Speech and Language Processing
An Introduction to Natural Language Processing,
Computational Linguistics, and Speech Recognition
Third Edition draft
Daniel Jurafsky
Stanford University
James H. Martin
University of Colorado at Boulder
Copyright ©2020. All rights reserved.
Draft of December 30, 2020. Comments and typos welcome!
Summary of Contents
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 Regular Expressions, Text Normalization, Edit Distance . . . . . . . . . 2
3 N-gram Language Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4 Naive Bayes and Sentiment Classification . . . . . . . . . . . . . . . . . . . . . . . 55
5 Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6 Vector Semantics and Embeddings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
7 Neural Networks and Neural Language Models . . . . . . . . . . . . . . . . . 127
8 Sequence Labeling for Parts of Speech and Named Entities . . . . . . 148
9 Deep Learning Architectures for Sequence Processing . . . . . . . . . . . 173
10 Contextual Embeddings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
11 Machine Translation and Encoder-Decoder Models . . . . . . . . . . . . . 203
12 Constituency Grammars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
13 Constituency Parsing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259
14 Dependency Parsing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280
15 Logical Representations of Sentence Meaning . . . . . . . . . . . . . . . . . . . 305
16 Computational Semantics and Semantic Parsing . . . . . . . . . . . . . . . . 331
17 Information Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332
18 Word Senses and WordNet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355
19 Semantic Role Labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
20 Lexicons for Sentiment, Affect, and Connotation . . . . . . . . . . . . . . . . 393
21 Coreference Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
22 Discourse Coherence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 442
23 Question Answering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464
24 Chatbots & Dialogue Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492
25 Phonetics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526
26 Automatic Speech Recognition and Text-to-Speech . . . . . . . . . . . . . . 548
Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 575
Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607
https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf
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Speech and Language Processing An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Speech and Language Processing An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition Third Editi...
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Chapter 1 Language Processing and Python 1 Chapter 2 Accessing Text Corpora and Lexical Resources 39 Chapter 3 Processing Raw Text 79 Chapt...
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Contents III Data Preparation 34 IV BagofWords 61 V Word Embeddings 114 VI Text Classification 144 VII Language Modeling 189 VIII Image Ca...
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Part I. The Fundamentals of Machine Learning 1. The Machine Learning Landscape. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
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