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Foreword | ||
1 | Introduction | 1 |
1.1 | What this book is about | 1 |
1.2 | Speech recognition and language models | 5 |
1.3 | What Regulus does | 13 |
1.4 | Clarissa and MedSLT | 15 |
1.5 | Related work | 20 |
1.6 | Plan of the book | 20 |
1.7 | Summary | 21 |
I | Using Regulus | 23 |
2 | Getting started | 25 |
2.1 | Getting set up | 25 |
2.2 | A toy grammar in GSL | 28 |
2.3 | Rewriting Toy0 in Regulus | 32 |
2.4 | Regulus configuration files | 37 |
2.5 | Using Regulus | 39 |
2.6 | Summary | 40 |
3 | Simple applications | 43 |
3.1 | Introduction | 43 |
3.2 | The Regulus Speech Server | 44 |
3.3 | A toy dialogue system in Prolog | 46 |
3.4 | A toy speech translation system in Prolog | 50 |
3.5 | A toy dialogue system in Java | 53 |
3.6 | Summary | 62 |
4 | Developing grammars | 65 |
4.1 | Introduction | 65 |
4.2 | Using the Regulus development environment | 65 |
4.3 | The Toy1 example grammar | 67 |
4.4 | Unification | 77 |
4.5 | Macros | 81 |
4.6 | Compiling the Toy1 recogniser | 85 |
4.7 | Systematic testing of recognisers | 87 |
4.8 | Summary | 89 |
5 | A spoken dialogue system | 93 |
5.1 | Introduction | 93 |
5.2 | The Toy1 spoken dialogue system | 95 |
5.3 | The input manager | 102 |
5.4 | The dialogue manager | 104 |
5.5 | The output manager | 108 |
5.6 | Integrating dialogue management with recognition | 108 |
5.7 | Dealing with ellipsis and corrections | 112 |
5.8 | Summary | 117 |
6 | A speech translation system | 119 |
6.1 | Introduction | 119 |
6.2 | Transfer-based systems | 120 |
6.3 | Developing translation applications | 127 |
6.4 | Translation through interlingua | 132 |
6.5 | Translation of ellipsis | 134 |
6.6 | Systematic development | 138 |
6.7 | Integrating translation with recognition | 142 |
6.8 | Summary | 145 |
7 | Using grammar specialisation | 149 |
7.1 | Overview | 149 |
7.2 | Using the general English grammar | 150 |
7.3 | The training corpus | 154 |
7.4 | Adding lexical entries | 156 |
7.5 | General grammar semantics | 166 |
7.6 | Multiple top-level specialised grammars | 169 |
7.7 | Including lexicon entries directly | 169 |
7.8 | Dealing with ambiguity | 171 |
7.9 | Making compilation more efficient | 171 |
7.10 | Using probabilistic tuning | 172 |
7.11 | Summary | 173 |
II | How Regulus Works | 175 |
8 | Compiling feature grammars into CFG | 177 |
8.1 | Introduction | 177 |
8.2 | Exhaustive expansion | 178 |
8.3 | Filtering | 179 |
8.4 | Efficient filtering of CFGs | 182 |
8.5 | Interleaving expansion and filtering | 186 |
8.6 | Pre-processing of feature grammars | 195 |
8.7 | Transforming the output CFG | 199 |
8.8 | Semantics | 203 |
8.9 | Summary | 203 |
9 | A general English feature grammar for speech | 205 |
9.1 | Introduction | 205 |
9.2 | What makes speech grammars special | 206 |
9.3 | English grammar: basic intuitions | 206 |
9.4 | Compositional semantics | 209 |
9.5 | Noun phrases | 211 |
9.6 | Verb phrases and basic clauses | 214 |
9.7 | Adjuncts | 228 |
9.8 | Coordination | 229 |
9.9 | Feature defaults | 230 |
9.10 | Summary | 231 |
10 | Grammar specialisation using Explanation Based Learning | 233 |
10.1 | Explanation Based Learning | 233 |
10.2 | Defining cutting-up criteria | 244 |
10.3 | Different kinds of cutting-up criteria | 246 |
10.4 | Summary | 251 |
11 | Performance of grammar-based recognisers | 255 |
11.1 | Introduction | 255 |
11.2 | Varying vocabulary size | 256 |
11.3 | Varying linguistic coverage | 259 |
11.4 | Varying the feature set | 261 |
11.5 | Varying the cutting-up criteria | 263 |
11.6 | Comparing CFG and PCFG language models | 266 |
11.7 | Deriving recognisers from general grammars | 267 |
11.8 | Summary | 268 |
12 | Comparison of rule-based and robust approaches | 271 |
12.1 | Introduction | 271 |
12.2 | Methodological issues | 272 |
12.3 | Experiments on MedSLT | 279 |
12.4 | Experiments on Clarissa | 281 |
12.5 | Discussion | 282 |
12.6 | Summary | 286 |
13 | Summary and future directions | 289 |
13.1 | Summary | 289 |
13.2 | Future directions | 291 |
Appendix | Online Documentation | 293 |
References | 295 | |
Index | 301 |
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Add Putting Linguistics into Speech Recognition: The Regulus Grammar Compiler, Most computer programs that analyze spoken dialogue use a spoken command grammar, which limits what the user can say when talking to the system. To make this process simpler, more automated, and effective for command grammars even at initial stages of a p, Putting Linguistics into Speech Recognition: The Regulus Grammar Compiler to the inventory that you are selling on WonderClubX
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Add Putting Linguistics into Speech Recognition: The Regulus Grammar Compiler, Most computer programs that analyze spoken dialogue use a spoken command grammar, which limits what the user can say when talking to the system. To make this process simpler, more automated, and effective for command grammars even at initial stages of a p, Putting Linguistics into Speech Recognition: The Regulus Grammar Compiler to your collection on WonderClub |