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Linear Prediction of Speech: Communication and Cybernetics, cartea 12

Autor J. D. Markel, A. H. Jr. Gray
en Limba Engleză Paperback – 15 noi 2011
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.
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Specificații

ISBN-13: 9783642662881
ISBN-10: 3642662889
Pagini: 304
Ilustrații: XII, 290 p.
Dimensiuni: 170 x 244 x 16 mm
Greutate: 0.49 kg
Ediția:Softcover reprint of the original 1st ed. 1976
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Communication and Cybernetics

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.