Crowdsourcing for speech processing : applications to data collection, transcription and assessment /

• Άλλοι συγγραφείς: Levow, Gina-Anne, Meng, Helen, Parent, Gabriel, Suendermann, David
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York : Wiley, 2013.
• Θέματα: Speech processing systems > Research.; Human computation.; Data mining.; COMPUTERS > Optical Data Processing.; 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 u...

Πίνακας περιεχομένων:

• 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.