Language and Computers

Language and Computers: Markus Dickinson, Chris Brew and Detmar Meurers......Page 5
Brief Contents......Page 7
Contents......Page 9
What This Book Is About......Page 13
Overview for Instructors......Page 15
Acknowledgments......Page 19
1.1 Where do we start?......Page 21
1.2 Writing systems used for human languages......Page 22
1.2.1 Alphabetic systems......Page 23
1.2.2 Syllabic systems......Page 26
1.2.3 Logographic writing systems......Page 28
1.2.5 Relation to language......Page 31
1.3.1 Storing information on a computer......Page 32
1.3.2 Using bytes to store characters......Page 34
1.4.1 The nature of speech......Page 37
1.4.3 Acoustic properties......Page 38
1.4.4 Measuring speech......Page 40
1.4.5 Relating written and spoken language......Page 44
Under the Hood 2: Language modeling for automatic speech recognition......Page 46
2.1 Introduction......Page 53
2.2 Kinds of spelling errors......Page 54
2.2.1 Nonword errors......Page 55
2.2.2 Real-word errors......Page 57
2.3 Spell checkers......Page 58
2.3.1 Nonword error detection......Page 59
2.3.2 Isolated-word spelling correction......Page 61
Under the Hood 3: Dynamic programming......Page 64
2.4 Word correction in context......Page 69
2.4.1 What is grammar?......Page 70
Under the Hood 4: Complexity of languages......Page 76
2.4.2 Techniques for correcting words in context......Page 78
Under the Hood 5: Spell checking for web queries......Page 82
2.5 Style checkers......Page 84
3.1 Learning a language......Page 89
3.2 Computer-assisted language learning......Page 91
3.3 Why make CALL tools aware of language?......Page 93
3.4.1 Tokenization......Page 96
3.4.2 Part-of-speech tagging......Page 98
3.4.3 Beyond words......Page 100
3.5 An example ICALL system: TAGARELA......Page 101
3.6 Modeling the learner......Page 103
4.1 Introduction......Page 111
4.2 Searching through structured data......Page 113
4.3.1 Information need......Page 115
4.3.2 Evaluating search results......Page 116
4.3.3 Example: Searching the web......Page 117
4.3.4 How search engines work......Page 120
Under the Hood 6: A brief tour of HTML......Page 123
4.4 Searching semi-structured data with regular expressions......Page 127
4.4.1 Syntax of regular expressions......Page 128
4.4.2 Grep: An example of using regular expressions......Page 130
Under the Hood 7: Finite-state automata......Page 132
4.5 Searching text corpora......Page 135
4.5.1 Why corpora?......Page 136
4.5.2 Annotated language corpora......Page 137
Under the Hood 8: Searching for linguistic patterns on the web......Page 138
5.1 Automatic document classification......Page 147
5.2 How computers “learn ”......Page 149
5.2.1 Supervised learning......Page 150
5.3 Features and evidence......Page 151
5.4 Application: Spam filtering......Page 153
5.4.1 Base rates......Page 155
5.4.3 Back to documents......Page 159
5.5.1 The Naive Bayes classifier......Page 160
Under the Hood 9: Naive Bayes......Page 162
5.5.2 The perceptron......Page 165
5.5.3 Which classifier to use......Page 168
5.6 From classification algorithms to context of use......Page 169
6.1 Computers that “converse”?......Page 173
6.2 Why dialogs happen......Page 175
6.3.1 Getting started......Page 176
6.3.3 Accepting the user’s goal......Page 177
6.3.5 Giving the answer......Page 178
6.4 Conventions and framing expectations......Page 179
6.4.2 The framing expectations for dialogs......Page 180
6.5.1 Dialog moves......Page 181
6.5.2 Speech acts......Page 182
6.5.3 Conversational maxims......Page 184
6.6 Dialog systems and their tasks......Page 186
6.7 Eliza......Page 187
Under the Hood 10: How Eliza works......Page 192
6.8 Spoken dialogs......Page 194
6.9 How to evaluate a dialog system......Page 195
6.10 Why is dialog important?......Page 196
7.1 Computers that “translate”?......Page 201
7.2.1 Translation needs......Page 203
7.2.2 What is machine translation really for?......Page 204
7.3 Translating Shakespeare......Page 205
7.4 The translation triangle......Page 208
7.5 Translation and meaning......Page 211
7.6.1 Words and other languages......Page 213
7.7 Word alignment......Page 214
7.8 IBM Model 1......Page 218
Under the Hood 11: The noisy channel model......Page 220
Under the Hood 12: Phrase-based statistical translation......Page 224
7.9.1 Translating weather reports......Page 225
7.9.2 Translation in the European Union......Page 227
7.9.3 Prospects for translators......Page 228
8 Epilogue: Impact of Language Technology......Page 235
References......Page 241
Concept Index......Page 247