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Phonetic analysis of speech corpora

Phonetic analysis of speech corpora (3회 대출)

자료유형
단행본
개인저자
Harrington, Jonathan, 1950-.
서명 / 저자사항
Phonetic analysis of speech corpora / Jonathan Harrington.
발행사항
Chichester, U.K. ;   Malden, MA :   Wiley-Blackwell,   c2010.  
형태사항
xx, 403 p. : ill. ; 26 cm.
ISBN
9781405199575 (pbk.) 1405199571 (pbk.) 9781405141697 1405141697
서지주기
Includes bibliographical references (p. [381]-393) and index.
일반주제명
Speech processing systems. Phonetics. Speech -- Research.
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001 000045617703
005 20101118105745
008 101116s2010 enka b 001 0 eng d
010 ▼a 2010279267
015 ▼a GBA728837 ▼2 bnb
020 ▼a 9781405199575 (pbk.)
020 ▼a 1405199571 (pbk.)
020 ▼a 9781405141697
020 ▼a 1405141697
035 ▼a (OCoLC)ocn123375074
040 ▼a UKM ▼c UKM ▼d BAKER ▼d BTCTA ▼d YDXCP ▼d OCLCG ▼d BWKUK ▼d BWK ▼d BWX ▼d DLC ▼d 211009
050 0 0 ▼a P95.3 ▼b .H37 2010
082 0 4 ▼a 414.8 ▼2 22
084 ▼a 414.8 ▼2 DDCK
090 ▼a 414.8 ▼b H299p
100 1 ▼a Harrington, Jonathan, ▼d 1950-.
245 1 0 ▼a Phonetic analysis of speech corpora / ▼c Jonathan Harrington.
260 ▼a Chichester, U.K. ; ▼a Malden, MA : ▼b Wiley-Blackwell, ▼c c2010.
300 ▼a xx, 403 p. : ▼b ill. ; ▼c 26 cm.
504 ▼a Includes bibliographical references (p. [381]-393) and index.
650 0 ▼a Speech processing systems.
650 0 ▼a Phonetics.
650 0 ▼a Speech ▼x Research.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 414.8 H299p 등록번호 111599906 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

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.


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