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Phonetic Analysis of Speech Corpora / Edition 1

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Overview

Phonetic Analysis of Speech Corpora introduces methods of analyzing phonetically labeled speech corpora, with the goal of testing hypotheses that often arise in experimental phonetics and laboratory phonology. The book begins by discussing some of the techniques in digital speech processing and in structuring and querying annotations from speech corpora. The second half of the book focuses on analysis, including measuring gestural synchronization using electromagnetic articulometry (EMA), the acoustics of vowels, consonant overlap using electropalatography (EPG), spectral analysis of fricatives and obstruents, and the probabilistic classification of acoustic speech data.

Each chapter has an extensive set of exercises, with answers to reinforce the techniques introduced. An overview of the necessary software tools, including the R programming language, enables the reader to duplicate the stages of analysis computationally. Clearly laid out, with easy-to-follow computer commands, spectrograms of speech corpora, and a companion website with more illustrations and downloadable speech corpora for testing purposes, this book is a complete resource for the research increasingly conducted in phonetics.

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Editorial Reviews

From the Publisher
"The book undoubtedly succeeds entirely in its goal to provide an accessible and effective practical introduction to using Emu speech database system and Emu-R functions to analyze phonetic data. It is written in a clear and accessible language and the topics are introduced in a coherent and easy to follow manner with the complexity of the material gradually increasing from the beginning towards the end of the book. Even rather complicated concepts are made easy to understand with an exceptional use of analogy and a commendable restraint from going into too many mathematical and technical details...this is a well-written, well-structured, easy-to-follow workbook which boasts an excellent set of practical exercises and demonstrations and covers a wide range of techniques. Overall, those readers who have a basic background in phonetics and statistics and are prepared to work their way carefully through this book will be greatly rewarded with its informativeness and effectiveness." (LINGUIST List, January 2011)
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Product Details

  • ISBN-13: 9781405141697
  • Publisher: Wiley
  • Publication date: 4/19/2010
  • Edition number: 1
  • Pages: 424
  • Product dimensions: 6.60 (w) x 9.80 (h) x 1.10 (d)

Meet the Author

Jonathan Harrington is Professor of the Institute of Phonetics and Speech Processing (IPS), University of Munich, Germany. His recent research has primarily focused on modelling the acoustic and perceptual mechanisms of sound change. He is co-editor of Speech Production: Models, Phonetic Processes, and Techniques (with Marija Tabain, 2006) and Techniques in Speech Acoustics (with Steve Cassidy, 1999).

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Table of Contents

Relationship between Machine Readable (MRPA) and International Phonetic Alphabet (IPA) for Australian English x

Relationship between Machine Readable (MRPA) and International Phonetic Alphabet (IPA) for German xii

Downloadable Speech Databases Used in this Book xiv

Preface xvi

Notes on Downloading Software xix

Chapter 1 Using Speech Corpora in Phonetics Research 1

1.1 The Place of Corpora in the Phonetic Analysis of Speech 1

1.2 Existing Speech Corpora for Phonetic Analysis 4

1.3 Designing Your Own Corpus 6

1.4 Summary and Structure of the Book 18

Chapter 2 Some Tools for Building and Querying Annotated Speech Databases 20

2.1 Overview 20

2.2 Getting Started with Existing Speech Databases 21

2.3 Interface between Praat and Emu 24

2.4 Interface to R 26

2.5 Creating a New Speech Database: From Praat to Emu to R 32

2.6 A First Look at the Template File 34

2.7 Summary 38

2.8 Questions 39

Chapter 3 Applying Routines for Speech Signal Processing 46

3.1 Introduction 46

3.2 Calculating, Displaying, and Correcting Formants 48

3.3 Reading the Formants into R 53

3.4 Summary 58

3.5 Questions 59

3.6 Answers 69

Chapter 4 Querying Annotation Structures 72

4.1 The Emu Query Tool, Segment Tiers, and Event Tiers 72

4.2 Extending the Range of Queries: Annotations from the Same Tier 74

4.3 Inter-tier Links and Queries 77

4.4 Entering Structured Annotations with Emu 82

4.5 Conversion of a Structured Annotation to a Praat TextGrid 86

4.6 Graphical User Interface to the Emu Query Language 88

4.7 Re-querying Segment Lists 90

4.8 Building Annotation Structures Semi-automatically with Emu-Tcl 91

4.9 Branching Paths 97

4.10 Summary 101

4.11 Questions 103

4.12 Answers 108

Chapter 5 An Introduction to Speech Data Analysis in R: A Study of an EMA Database 115

5.1 EMA Recordings and the ema5 Database 116

5.2 Handling Segment Lists and Vectors in Emu-R 121

5.3 An Analysis of Voice-Onset Time 125

5.4 Intergestural Coordination and Ensemble Plots 132

5.5 Intragestural Analysis 139

5.6 Summary 159

5.7 Questions 161

5.8 Answers 164

Chapter 6 Analysis of Formants and Formant Transitions 171

6.1 Vowel Ellipses in the F2 x F1 Plane 172

6.2 Outliers 177

6.3 Vowel Targets 179

6.4 Vowel Normalization 183

6.5 Euclidean Distances 190

6.6 Vowel Undershoot and Formant Smoothing 198

6.7 F2 Locus, Place of Articulation, and Variability 206

6.8 Questions 213

6.9 Answers 216

Chapter 7 Electropalatography 220

7.1 Palatography and Electropalatography 220

7.2 An Overview of Electropalatography in Emu-R 222

7.3 EPG Data-Reduced Objects 234

7.4 Analysis of EPG Data 248

7.5 Summary 258

7.6 Questions 259

7.7 Answers 260

Chapter 8 Spectral Analysis 264

8.1 Background to Spectral Analysis 264

8.2 Spectral Average, Sum, Ratio, Difference, Slope 288

8.3 Spectral Moments 297

8.4 The Discrete Cosine Transformation 304

8.5 Questions 316

8.6 Answers 320

Chapter 9 Classification 327

9.1 Probability and Bayes' Theorem 327

9.2 Classification: Continuous Data 330

9.3 Calculating Conditional Probabilities 336

9.4 Calculating Posterior Probabilities 338

9.5 Two Parameters: The Bivariate Normal Distribution and Ellipses 342

9.6 Classification in Two Dimensions 347

9.7 Classifications in Higher Dimensional Spaces 352

9.8 Classifications in Time 359

9.9 Support Vector Machines 366

9.10 Summary 373

9.11 Questions 374

9.12 Answers 377

References 381

Index 394

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