Contents
List of Contributors xiii
Preface xv
1 An Overview 1
Maxine Eskenazi
1.1 Origins of Crowdsourcing 2
1.2 Operational Definition of Crowdsourcing 3
1.3 Functional Definition of Crowdsourcing 3
1.4 Some Issues 4
1.5 Some Terminology 6
1.6 Acknowledgments 6
References 6
2 The Basics 8
Maxine Eskenazi
2.1 An Overview of the Literature on Crowdsourcing for Speech Processing 8
2.2 Alternative Solutions 14
2.3 Some Ready-Made Platforms for Crowdsourcing 15
2.4 Making Task Creation Easier 17
2.5 Getting Down to Brass Tacks 17
2.6 Quality Control 29
2.7 Judging the Quality of the Literature 32
2.8 Some Quick Tips 33
2.9 Acknowledgments 33
References 33
Further reading 35
3 Collecting Speech from Crowds 37
Ian McGraw
3.1 A Short History of Speech Collection 38
3.2 Technology for Web-Based Audio Collection 43
3.3 Example: WAMI Recorder 49
3.4 Example: The WAMI Server 52
3.5 Example: Speech Collection on Amazon Mechanical Turk 59
3.6 Using the Platform Purely for Payment 65
3.7 Advanced Methods of Crowdsourced Audio Collection 67
3.8 Summary 69
3.9 Acknowledgments 69
References 70
4 Crowdsourcing for Speech Transcription 72
Gabriel Parent
4.1 Introduction 72
4.2 Transcribing Speech 73
4.3 Preparing the Data 80
4.4 Setting Up the Task 83
4.5 Submitting the Open Call 91
4.6 Quality Control 95
4.7 Conclusion 102
4.8 Acknowledgments 103
References 103
5 How to Control and Utilize Crowd-Collected Speech 106
Ian McGraw and Joseph Polifroni
5.1 Read Speech 107
5.2 Multimodal Dialog Interactions 111
5.3 Games for Speech Collection 120
5.4 Quizlet 121
5.5 Voice Race 123
5.6 Voice Scatter 129
5.7 Summary 135
5.8 Acknowledgments 135
References 136
6 Crowdsourcing in Speech Perception 137
Martin Cooke, Jon Barker, and Maria Luisa Garcia Lecumberri
6.1 Introduction 137
6.2 Previous Use of Crowdsourcing in Speech and Hearing 138
6.3 Challenges 140
6.4 Tasks 145
6.5 BigListen: A Case Study in the Use of Crowdsourcing to Identify Words in Noise 149
6.6 Issues for Further Exploration 167
6.7 Conclusions 169
References 169
7 Crowdsourced Assessment of Speech Synthesis 173
Sabine Buchholz, Javier Latorre, and Kayoko Yanagisawa
7.1 Introduction 173
7.2 Human Assessment of TTS 174
7.3 Crowdsourcing for TTS: What Worked and What Did Not 177
7.4 Related Work: Detecting and Preventing Spamming 193
7.5 Our Experiences: Detecting and Preventing Spamming 195
7.6 Conclusions and Discussion 212
References 214
8 Crowdsourcing for Spoken Dialog System Evaluation 217
Zhaojun Yang, Gina-Anne Levow, and Helen Meng
8.1 Introduction 217
8.2 Prior Work on Crowdsourcing: Dialog and Speech Assessment 220
8.3 Prior Work in SDS Evaluation 221
8.4 Experimental Corpus and Automatic Dialog Classification 225
8.5 Collecting User Judgments on Spoken Dialogs with Crowdsourcing 226
8.6 Collected Data and Analysis 230
8.7 Conclusions and Future Work 238
8.8 Acknowledgments 238
References 239
9 Interfaces for Crowdsourcing Platforms 241
Christoph Draxler
9.1 Introduction 241
9.2 Technology 242
9.3 Crowdsourcing Platforms 253
9.4 Interfaces to Crowdsourcing Platforms 261
9.5 Summary 278
References 278
10 Crowdsourcing for Industrial Spoken Dialog Systems 280
David Suendermann and Roberto Pieraccini
10.1 Introduction 280
10.2 Architecture 283
10.3 Transcription 287
10.4 Semantic Annotation 290
10.5 Subjective Evaluation of Spoken Dialog Systems 296
10.6 Conclusion 300
References 300
11 Economic and Ethical Background of Crowdsourcing for Speech 303
Gilles Adda, Joseph J. Mariani, Laurent Besacier, and Hadrien Gelas
11.1 Introduction 303
11.2 The Crowdsourcing Fauna 304
11.3 Economic and Ethical Issues 307
11.4 Under-Resourced Languages: A Case Study 316
11.5 Toward Ethically Produced Language Resources 322
11.6 Conclusion 330
Disclaimer 331
References 331
Index 335
