Phonetic Analysis of Speech Corpora

by Harrington, Jonathan

• ISBN13: 9781405199575
• ISBN10: 1405199571
• Edition: 1st
• Format: Paperback
• Copyright: 2010-04-12
• Publisher: Wiley-Blackwell

Summary

An accessible introduction to the phonetic analysis of speech corpora, this workbook-style text provides an extensive set of exercises to help readers develop the necessary skills to design and carry out experiments in speech research. Offers the first step-by-step treatment of advanced techniques in experimental phonetics using speech corpora and downloadable software, including the R programming language Introduces methods of analyzing phonetically-labelled speech corpora, with the goal of testing hypotheses that often arise in experimental phonetics and laboratory phonology Incorporates an extensive set of exercises and answers to reinforce the techniques introduced Accessibly written with easy-to-follow computer commands, spectrograms of speech corpora, and website resources including illustrations and downloadable speech corpora for testing purposes Discusses techniques in digital speech processing and in structuring and querying annotations from speech corpora Includes substantial coverage of analysis, including measuring gestural synchronization using EMA, the acoustics of vowels, consonant overlap using EPG, spectral analysis of fricatives and obstruents, and the probabilistic classification of acoustic speech data

Author Biography

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).

Table of Contents

Preface

Notes on Downloading Software

Using Speech Corpora in Phonetics Research

The Place of Corpora in the Phonetic Analysis of Speech

Existing Speech Corpora for Phonetic Analysis

Designing Your Own Corpus

Summary and Structure of the Book

Some Tools for Building and Querying Annotated Speech Databases

Overview

Getting Started with Existing Speech Databases

Interface between Praat and Emu

Interface to R

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

A First Look at the Template File

Summary

Questions

Applying Routines for Speech Signal Processing

Introduction

Calculating, Displaying, and Correcting Formants

Reading the Formants into R

Summary

Questions

Answers

Querying Annotation Structures

The Emu Query Tool, Segment Tiers, and Event Tiers

Extending the Range of Queries: Annotations from the Same Tier

Inter-tier Links and Queries

Entering Structured Annotations with Emu

Conversion of a Structured Annotation to a Praat TextGrid

Graphical User Interface to the Emu Query Language

Re-querying Segment Lists

Building Annotation Structures Semi-automatically with Emu-Tcl

Branching Paths

Summary

Questions

Answers

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

EMA

Recordings and the ema5 Database

Handling Segment Lists and Vectors in Emu-R

An Analysis of Voice-Onset Time

Intergestural Coordination and Ensemble Plots

Intragestural Analysis

Summary

Questions

Answers

Analysis of Formants and Formant Transitions

Vowel Ellipses in the F2íF1 Plane

Outliers

Vowel Targets

Vowel Normalization

Euclidean Distances

Vowel Undershoot and Formant Smoothing

F2 Locus, Place of Articulation, and Variability

Questions

Answers

Electropalatography

Palatography and Electropalatography

An Overview of Electropalatography in Emu-R

EPG Data-Reduced Objects

Analysis of EPG Data

Summary

Questions

Answers

Spectral Analysis

Background to Spectral Analysis

Spectral Average, Sum, Ratio, Difference, Slope

Spectral Moments

The Discrete Cosine Transformation

Questions

Answers

Classification

Probability and Bayes' Theorem

Classification: Continuous Data

Calculating Conditional Probabilities

Calculating Posterior Probabilities

Two Parameters: The Bivariate Normal Distribution and Ellipses

Classification in Two Dimensions

Classifications in Higher Dimensional Spaces

Classifications in Time

Support Vector Machines

Summary

Questions

Answers

References

Index

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