Crowdsourcing for speech processing [electronic resource] : applications to data collection, transcription and assessment / editors, Maxine Eskénazi ... [et al.].

Chichester : Wiley, 2013.
1 online resource (358 p.)

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Speech processing systems -- Research.
Human computation.
Data mining.
Electronic books.
Provides an insightful and practical introduction to crowdsourcing as a means of rapidly processing speech data Intended for those who want to get started in the domain and learn how to set up a task, what interfaces are available, how to assess the work, etc. as well as for those who already have used crowdsourcing and want to create better tasks and obtain better assessments of the work of the crowd. It will include screenshots to show examples of good and poor interfaces; examples of case studies in speech processing tasks, going through the task creation process, re
CROWDSOURCING FOR SPEECH PROCESSING; Contents; List of Contributors; Preface; 1 An Overview; 1.1 Origins of Crowdsourcing; 1.2 Operational Definition of Crowdsourcing; 1.3 Functional Definition of Crowdsourcing; 1.4 Some Issues; 1.5 Some Terminology; 1.6 Acknowledgments; References; 2 The Basics; 2.1 An Overview of the Literature on Crowdsourcing for Speech Processing; 2.1.1 Evolution of the Use of Crowdsourcing for Speech; 2.1.2 Geographic Locations of Crowdsourcing for Speech; 2.1.3 Specific Areas of Research; 2.2 Alternative Solutions; 2.3 Some Ready-Made Platforms for Crowdsourcing
2.4 Making Task Creation Easier2.5 Getting Down to Brass Tacks; 2.5.1 Hearing and Being Heard over the Web; 2.5.2 Prequalification; 2.5.3 Native Language of the Workers; 2.5.4 Payment; 2.5.5 Choice of Platform in the Literature; 2.5.6 The Complexity of the Task; 2.6 Quality Control; 2.6.1 Was That Worker a Bot?; 2.6.2 Quality Control in the Literature; 2.7 Judging the Quality of the Literature; 2.8 Some Quick Tips; 2.9 Acknowledgments; References; Further reading; 3 Collecting Speech from Crowds; 3.1 A Short History of Speech Collection; 3.1.1 Speech Corpora; 3.1.2 Spoken Language Systems
3.1.3 User-Configured Recording Environments3.2 Technology for Web-Based Audio Collection; 3.2.1 Silverlight; 3.2.2 Java; 3.2.3 Flash; 3.2.4 HTML and JavaScript; 3.3 Example: WAMI Recorder; 3.3.1 The JavaScript API; 3.3.2 Audio Formats; 3.4 Example: The WAMI Server; 3.4.1 PHP Script; 3.4.2 Google App Engine; 3.4.3 Server Configuration Details; 3.5 Example: Speech Collection on Amazon Mechanical Turk; 3.5.1 Server Setup; 3.5.2 Deploying to Amazon Mechanical Turk; 3.5.3 The Command-Line Interface; 3.6 Using the Platform Purely for Payment; 3.7 Advanced Methods of Crowdsourced Audio Collection
3.7.1 Collecting Dialog Interactions3.7.2 Human Computation; 3.8 Summary; 3.9 Acknowledgments; References; 4 Crowdsourcing for Speech Transcription; 4.1 Introduction; 4.1.1 Terminology; 4.2 Transcribing Speech; 4.2.1 The Need for Speech Transcription; 4.2.2 Quantifying Speech Transcription; 4.2.3 Brief History; 4.2.4 Is Crowdsourcing Well Suited to My Needs?; 4.3 Preparing the Data; 4.3.1 Preparing the Audio Clips; 4.3.2 Preprocessing the Data with a Speech Recognizer; 4.3.3 Creating a Gold-Standard Dataset; 4.4 Setting Up the Task; 4.4.1 Creating Your Task with the Platform Template Editor
4.4.2 Creating Your Task on Your Own Server4.4.3 Instruction Design; 4.4.4 Know the Workers; 4.4.5 Game Interface; 4.5 Submitting the Open Call; 4.5.1 Payment; 4.5.2 Number of Distinct Judgments; 4.6 Quality Control; 4.6.1 Normalization; 4.6.2 Unsupervised Filters; 4.6.3 Supervised Filters; 4.6.4 Aggregation Techniques; 4.6.5 Quality Control Using Multiple Passes; 4.7 Conclusion; 4.8 Acknowledgments; References; 5 How to Control and Utilize Crowd-Collected Speech; 5.1 Read Speech; 5.1.1 Collection Procedure; 5.1.2 Corpus Overview; 5.2 Multimodal Dialog Interactions; 5.2.1 System Design
5.2.2 Scenario Creation
Description based upon print version of record.
Includes bibliographical references and index.
Eskenazi, Maxine.