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    1. Språk och ordböcker
    2. Språkvetenskap och lingvistik

    Phonetic Analysis of Speech Corpora

    AvJonathan Harrington

    Häftad, Engelska, 2010

    565 kr

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    1 626 kr

    Beskrivning

    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 languageIntroduces methods of analyzing phonetically-labelled speech corpora, with the goal of testing hypotheses that often arise in experimental phonetics and laboratory phonologyIncorporates an extensive set of exercises and answers to reinforce the techniques introducedAccessibly written with easy-to-follow computer commands and spectrograms of speechCompanion website at www.wiley.com/go/harrington, which includes illustrations, video tutorials, appendices, and downloadable speech corpora for testing purposes.Discusses techniques in digital speech processing and in structuring and querying annotations from speech corporaIncludes 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

    Produktinformation

    • Utgivningsdatum:2010-03-12
    • Mått:196 x 241 x 25 mm
    • Vikt:748 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:432
    • Förlag:John Wiley and Sons Ltd
    • ISBN:9781405199575

    Utforska kategorier

    • Språkvetenskap och lingvistik inom Språk och ordböcker

    Mer om författaren

    Jonathan Harrington is Professor of the Institute of Phonetics and Speech Processing (IPS), Ludwig Maximilian University of Munich, Germany. His recent research has primarily focused on modeling 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).

    Recensioner i media

    "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)

    Innehållsförteckning

    • Relationship between Machine Readable (MRPA) and International Phonetic Alphabet (IPA) for Australian English. Relationship between Machine Readable (MRPA) and International Phonetic Alphabet (IPA) for German. Downloadable Speech Databases Used in this Book. Preface. Notes on Downloading Software. 1. Using Speech Corpora in Phonetics Research. 1.1 The Place of Corpora in the Phonetic Analysis of Speech. 1.2 Existing Speech Corpora for Phonetic Analysis. 1.3 Designing Your Own Corpus. 1.4 Summary and Structure of the Book. 2. Some Tools for Building and Querying Annotated Speech Databases. 2.1 Overview. 2.2 Getting Started with Existing Speech Databases. 2.3 Interface between Praat and Emu. 2.4 Interface to R. 2.5 Creating a New Speech Database: From Praat to Emu to R. 2.6 A First Look at the Template File. 2.7 Summary. 2.8 Questions. 3. Applying Routines for Speech Signal Processing. 3.1 Introduction. 3.2 Calculating, Displaying, and Correcting Formants. 3.3 Reading the Formants into R. 3.4 Summary. 3.5 Questions. 3.6 Answers. 4. Querying Annotation Structures. 4.1 The Emu Query Tool, Segment Tiers, and Event Tiers. 4.2 Extending the Range of Queries: Annotations from the Same Tier. 4.3 Inter-tier Links and Queries. 4.4 Entering Structured Annotations with Emu. 4.5 Conversion of a Structured Annotation to a Praat TextGrid. 4.6 Graphical User Interface to the Emu Query Language. 4.7 Re-querying Segment Lists. 4.8 Building Annotation Structures Semi-automatically with Emu-Tcl. 4.9 Branching Paths. 4.10 Summary. 4.11 Questions. 4.12 Answers. 5. An Introduction to Speech Data Analysis in R: A Study of an EMA Database. 5.1 EMA Recordings and the ema5 Database. 5.2 Handling Segment Lists and Vectors in Emu-R. 5.3 An Analysis of Voice-Onset Time. 5.4 Intergestural Coordination and Ensemble Plots. 5.5 Intragestural Analysis. 5.6 Summary. 5.7 Questions. 5.8 Answers. 6. Analysis of Formants and Formant Transitions. 6.1 Vowel Ellipses in the F2ÍF1 Plane. 6.2 Outliers. 6.3 Vowel Targets. 6.4 Vowel Normalization. 6.5 Euclidean Distances. 6.6 Vowel Undershoot and Formant Smoothing. 6.7 F2 Locus, Place of Articulation, and Variability. 6.8 Questions. 6.9 Answers. 7. Electropalatography. 7.1 Palatography and Electropalatography. 7.2 An Overview of Electropalatography in Emu-R. 7.3 EPG Data-Reduced Objects. 7.4 Analysis of EPG Data. 7.5 Summary. 7.6 Questions. 7.7 Answers. 8. Spectral Analysis. 8.1 Background to Spectral Analysis. 8.2 Spectral Average, Sum, Ratio, Difference, Slope. 8.3 Spectral Moments. 8.4 The Discrete Cosine Transformation. 8.5 Questions. 8.6 Answers. 9. Classification. 9.1 Probability and Bayes’ Theorem. 9.2 Classification: Continuous Data. 9.3 Calculating Conditional Probabilities. 9.4 Calculating Posterior Probabilities. 9.5 Two Parameters: The Bivariate Normal Distribution and Ellipses. 9.6 Classification in Two Dimensions. 9.7 Classifications in Higher Dimensional Spaces. 9.8 Classifications in Time. 9.9 Support Vector Machines. 9.10 Summary. 9.11 Questions. 9.12 Answers. References. Index.