Overview

During the past ten years a new area in speech processing, generally referred to as linear prediction, has evolved. As with all scientific research, results did not always get published in a logical order and terminology was not always con­ sistent. In mid-1974, we decided to begin an extra hours and weekends project of organizing the literature in linear prediction of speech and developing it into a unified presentation in terms of content and terminology. This effort was completed in November, 1975, with the contents presented herein. If there are two words which describe our goals in this book, they are unifica­ tion and depth. Considerable effort has been spent on showing the interrelation­ ships among various linear prediction formulations and solutions, and in develop­ ing extensions such as acoustic tube models and synthesis filter structures in a unified manner with consistent terminology. Topics are presented in such a manner that derivations and theoretical details are covered, along with Fortran sub­ routines and practical considerations. Using this approach we hope to have made the material useful for a wide range of backgrounds and interests.

Full Product Details

Author:   J.D. Markel ,  A.H. Jr. Gray
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 1st ed. 1976
Volume:   12
Dimensions:   Width: 17.00cm , Height: 1.60cm , Length: 24.40cm
Weight:   0.528kg
ISBN:  

9783642662881

ISBN 10:   3642662889
Pages:   290
Publication Date:   15 November 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

1. Introduction.- 1.1 Basic Physical Principles.- 1.2 Acoustical Waveform Examples.- 1.3 Speech Analysis and Synthesis Models.- 1.4 The Linear Prediction Model.- 1.5 Organization of Book.- 2. Formulations.- 2.1 Historical Perspective.- 2.2 Maximum Likelihood.- 2.3 Minimum Variance.- 2.4 Prony’s Method.- 2.5 Correlation Matching.- 2.6 PARCOR (Partial Correlation).- 3. Solutions and Properties.- 3.1 Introduction.- 3.2 Vector Spaces and Inner Products.- 3.3 Solution Algorithms.- 3.4 Matrix Forms.- 4. Acoustic Tube Modeling.- 4.1 Introduction.- 4.2 Acoustic Tube Derivation.- 4.3 Relationship between Acoustic Tube and Linear Prediction.- 4.4 An Algorithm, Examples, and Evaluation.- 4.5 Estimation of Lip Impedance.- 4.6 Further Topics.- 5. Speech Synthesis Structures.- 5.1 Introduction.- 5.2 Stability.- 5.3 Recursive Parameter Evaluation.- 5.4 A General Synthesis Structure.- 5.5 Specific Speech Synthesis Structures.- 6. Spectral Analysis.- 6.1 Introduction.- 6.2 Spectral Properties.- 6.3 A Spectral Flatness Model.- 6.4 Selective Linear Prediction.- 6.5 Considerations in Choice of Analysis Conditions.- 6.6 Spectral Evaluation Techniques.- 6.7 Pole Enhancement.- 7. Automatic Formant Trajectory Estimation.- 7.1 Introduction.- 7.2 Formant Trajectory Estimation Procedure.- 7.3 Comparison of Raw Data from Linear Prediction and Cepstral Smoothing.- 7.4 Algorithm 1.- 7.5 Algorithm 2.- 7.6 Formant Estimation Accuracy.- 8. Fundamental Frequency Estimation.- 8.1 Introduction.- 8.2 Preprocessing by Spectral Flattening.- 8.3 Correlation Techniques.- 9. Computational Considerations in Analysis.- 9.1 Introduction.- 9.2 Ill-Conditioning.- 9.3 Implementing Linear Prediction Analysis.- 9.4 Finite Word Length Considerations.- 10. Vocoders.- 10.1 Introduction.- 10.2 Techniques.- 10.3 Low BitRate Pitch Excited Vocoders.- 10.4 Base-Band Excited Vocoders.- 11. Further Topics.- 11.1 Speaker Identification and Verification.- 11.2 Isolated Word Recognition.- 11.3 Acoustical Detection of Laryngeal Pathology.- 11.4 Pole-Zero Estimation.- 11.5 Summary and Future Directions.- References.

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