Linear Prediction of Speech

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Product Details

  • ISBN-13: 9783642662881
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 11/15/2011
  • Series: Communication and Cybernetics Series, #12
  • Edition description: Softcover reprint of the original 1st ed. 1976
  • Edition number: 1
  • Pages: 290
  • Product dimensions: 6.69 (w) x 9.61 (h) x 0.64 (d)

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).- 2.6.1 Inner Products and an Orthogonality Principle.- 2.6.2 The PARCOR Lattice Structure.- 3. Solutions and Properties.- 3.1 Introduction.- 3.2 Vector Spaces and Inner Products.- 3.2.1 Filter or Polynomial Norms.- 3.2.2 Properties of Inner Products.- 3.2.3 Orthogonality Relations.- 3.3 Solution Algorithms.- 3.3.1 Correlation Matrix.- 3.3.2 Initialization.- 3.3.3 Gram-Schmidt Orthogonalization.- 3.3.4 Levinson Recursion.- 3.3.5 Updating Am(z).- 3.3.6 A Test Example.- 3.4 Matrix Forms.- 4. Acoustic Tube Modeling.- 4.1 Introduction.- 4.2 Acoustic Tube Derivation.- 4.2.1 Single Section Derivation.- 4.2.2 Continuity Conditions.- 4.2.3 Boundary Conditions.- 4.3 Relationship between Acoustic Tube and Linear Prediction.- 4.4 An Algorithm, Examples, and Evaluation.- 4.4.1 An Algorithm.- 4.4.2 Examples.- 4.4.3 Evaluation of the Procedure.- 4.5 Estimation of Lip Impedance.- 4.5.1 Lip Impedance Derivation.- 4.6 Further Topics.- 4.6.1 Losses in the Acoustic Tube Model.- 4.6.2 Acoustic Tube Stability.- 5. Speech Synthesis Structures.- 5.1 Introduction.- 5.2 Stability.- 5.2.1 Step-up Procedure.- 5.2.2 Step-down Procedure.- 5.2.3 Polynomial Properties.- 5.2.4 A Bound on |Fm(z)|.- 5.2.5 Necessary and Sufficient Stability Conditions.- 5.2.6 Application of Results.- 5.3 Recursive Parameter Evaluation.- 5.3.1 Inner Product Properties.- 5.3.2 Equation Summary with Program.- 5.4 A General Synthesis Structure.- 5.5 Specific Speech Synthesis Structures.- 5.5.1 The Direct Form.- 5.5.2 Two-Multiplier Lattice Model.- 5.5.3 Kelly-Lochbaum Model.- 5.5.4 One-Multiplier Models.- 5.5.5 Normalized Filter Model.- 5.5.6 A Test Example.- 6. Spectral Analysis.- 6.1 Introduction.- 6.2 Spectral Properties.- 6.2.1 Zero Mean All-Pole Model.- 6.2.2 Gain Factor for Spectral Matching.- 6.2.3 Limiting Spectral Match.- 6.2.4 Non-uniform Spectral Weighting.- 6.2.5 Minimax Spectral Matching.- 6.3 A Spectral Flatness Model.- 6.3.1 A Spectral Flatness Measure.- 6.3.2 Spectral Flatness Transformations.- 6.3.3 Numerical Evaluation.- 6.3.4 Experimental Results.- 6.3.5 Driving Function Models.- 6.4 Selective Linear Prediction.- 6.4.1 Selective Linear Prediction (SLP) Algorithm.- 6.4.2 A Selective Linear Prediction Program.- 6.4.3 Computational Considerations.- 6.5 Considerations in Choice of Analysis Conditions.- 6.5.1 Choice of Method.- 6.5.2 Sampling Rates.- 6.5.3 Order of Filter.- 6.5.4 Choice of Analysis Interval.- 6.5.5 Windowing.- 6.5.6 Pre-emphasis.- 6.6 Spectral Evaluation Techniques.- 6.7 Pole Enhancement.- 7. Automatic Formant Trajectory Estimation.- 7.1 Introduction.- 7.2 Formant Trajectory Estimation Procedure.- 7.2.1 Introduction.- 7.2.2 Raw Data from A(z).- 7.2.3 Examples of Raw Data.- 7.3 Comparison of Raw Data from Linear Prediction and Cepstral Smoothing.- 7.4 Algorithm 1.- 7.5 Algorithm 2.- 7.5.1 Definition of Anchor Points.- 7.5.2 Processing of Each Voiced Segment.- 7.5.3 Final Smoothing.- 7.5.4 Results and Discussion.- 7.6 Formant Estimation Accuracy.- 7.6.1 An Example of Synthetic Speech Analysis.- 7.6.2 An Example of Real Speech Analysis.- 7.6.3 Influence of Voice Periodicity.- 8. Fundamental Frequency Estimation.- 8.1 Introduction.- 8.2 Preprocessing by Spectral Flattening.- 8.2.1 Analysis of Voiced Speech with Spectral Regularity.- 8.2.2 Analysis of Voiced Speech with Spectral Irregularities.- 8.2.3 The STREAK Algorithm.- 8.3 Correlation Techniques.- 8.3.1 Auorrelation Analysis.- 8.3.2 Modified Auorrelation Analysis.- 8.3.3 Filtered Error Signal Auorrelation Analysis.- 8.3.4 Practical Considerations.- 8.3.5 The SIFT Algorithm.- 9. Computational Considerations in Analysis.- 9.1 Introduction.- 9.2 Ill-Conditioning.- 9.2.1 A Measure of Ill-Conditioning.- 9.2.2 Pre-emphasis of Speech Data.- 9.2.3 Prefiltering before Sampling.- 9.3 Implementing Linear Prediction Analysis.- 9.3.1 Auorrelation Method.- 9.3.2 Covariance Method.- 9.3.3 Computational Comparison.- 9.4 Finite Word Length Considerations.- 9.4.1 Finite Word Length Coefficient Computation.- 9.4.2 Finite Word Length Solution of Equations.- 9.4.3 Overall Finite Word Length Implementation.- 10. Vocoders.- 10.1 Introduction.- 10.2 Techniques.- 10.2.1 Coefficient Transformations.- 10.2.2 Encoding and Decoding.- 10.2.3 Variable Frame Rate Transmission.- 10.2.4 Excitation and Synthesis Gain Matching.- 10.2.5 A Linear Prediction Synthesizer Program.- 10.3 Low Bit Rate Pitch Excited Vocoders.- 10.3.1 Maximum Likelihood and PARCOR Vocoders.- 10.3.2 Auorrelation Method Vocoders.- 10.3.3 Covariance Method 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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