Mathematical modeling and signal processing in speech and hearing sciences /
Xin, Jack,
Mathematical modeling and signal processing in speech and hearing sciences / Jack Xin, Yingyong Qi. - xi, 206 pages : illustrations ; 24 cm. - MS&A, volume 10 2037-5263 ; . - MS&A (Series) ; v. 10. .
Includes bibliographical references (pages [189]-197) and index.
Machine generated contents note: 1.Background Signal Processing, Statistical and Optimization Methods -- 1.1.Introduction -- 1.2.Fourier and z-Transforms -- 1.2.1.Continuous Time Signals -- 1.2.2.Fourier Transform and Basic Properties -- 1.2.3.Discrete Time Signals and Systems -- 1.2.4.Sampling and Shannon Theory -- 1.2.5.Discrete Fourier Transform -- 1.2.6.Discrete Time and Windowed Fourier Transforms -- 1.2.7.Short Time Fourier Transform, Synthesis and Spectrogram -- 1.2.8.z-Transform -- 1.3.Filtering and Convolution -- 1.3.1.Circular Convolution -- 1.3.2.Linear Convolution and z-Transform -- 1.3.3.Circular Convolution and z-Transform -- 1.3.4.Rational Filters, Impulse and Frequency Responses -- 1.3.5.Group and Phase Delays -- 1.3.6.Minimum Phase and All Pass Filters -- 1.4.Random Variables, Correlation and Independence -- 1.4.1.Basic Notion and Examples -- 1.4.2.Joint Distribution and Independent Components -- 1.4.3.Random Number Generation -- 1.4.4.Stochastic Processes -- 1.4.5.Random Walk and Brownian Motion -- 1.5.Data Clustering and K-Means Method -- 1.6.Maximum Likelihood Method -- 1.7.Least Squares and Sparse Optimization Methods -- 1.8.Exercises -- 2.Speech Modeling -- 2.1.Introduction -- 2.2.Two Mass Vocal Fold Model -- 2.3.Matlab Program and Animation of Two Mass Model -- 2.4.Hydrodynamic Semi-Continuum Vocal Fold Model -- 2.5.Source-Filter Model of Speech Production -- 2.5.1.Uniform Lossless Tube Model and Transfer Function -- 2.5.2.Concatenated Lossless Tube Model: Traveling Waves and Transfer Function -- 2.5.3.Radiation and the Complete Model -- 2.5.4.Matlab Programs for Vowel and Consonant Synthesis -- 2.6.Exercises -- 3.Auditory Modeling -- 3.1.Introduction -- 3.2.Macromechanics and Passive Models -- 3.3.Micromechanics and Two Level Nonlocal Active Models -- 3.4.Dispersion and Decay Properties of Plane Waves -- 3.5.Time Harmonic Solutions -- 3.6.Asymptotic and Transform Techniques -- 3.7.Logarithmic Scales and Critical Bands -- 3.8.Time Demain Method and Dispersive Instability -- 3.9.Boundary Integral Method and Suppression of Instability -- 3.10.Computational Methods of Nonlocal Active Models -- 3.11.Nonlinear Phenomena and Sound Masking -- 3.12.Invertible Auditory Transforms -- 3.13.Orthogonal Auditory Transforms -- 3.14.Modeling Masking Thresholds -- 3.15.Modeling Hearing Loss and Hearing Aids -- 3.16.Matlab Programs -- 3.17.Exercises -- 4.Speech Recognition -- 4.1.Introduction -- 4.2.Hidden Markov Model (HMM) for Speech Processing -- 4.2.1.Speech Spectral Analysis -- 4.2.2.Vector Quantization -- 4.3.HMM for Isolated Word Recognition -- 4.3.1.Forward and Backward Probabilities -- 4.3.2.Baum-Welch Re-Estimation -- 4.3.3.Viterbi Decoding -- 4.4.Summary of Matlab Programs -- 4.5.Chapter Summary -- 4.6.Matlab Programs -- 4.7.Exercises -- 5.Blind Source Separation and Speech Enhancement -- 5.1.Introduction -- 5.2.Instantaneous Mixture and Decorrelation Methods -- 5.2.1.Decorrelation with Second Order Statistics -- 5.2.2.Demixing with Joint Second and Third Order Statistics -- 5.3.Instantaneous Mixture and Cumulant Method -- 5.3.1.Moments and Cumulants -- 5.3.2.Source Recovery and Whitening Process -- 5.3.3.Unitary Factor as Joint Diagonalizer of Cumulant Matrices -- 5.3.4.Joint Diagonalization of Eigenmatrices -- 5.3.5.Jacobi Method and Joint Diagonalizer Formula -- 5.4.Instantaneous Mixture and Infomax Methods -- 5.4.1.Statistical Equations for Source Separation -- 5.4.2.Iterative Methods -- 5.4.3.Uniform Bounds -- 5.4.4.Convergence and Source Separation -- 5.4.5.Numerical Example -- 5.5.Convolutive Mixture and Decorrelation Method -- 5.5.1.Decorrelation Equations -- 5.5.2.Constrained and Penalized Optimization -- 5.5.3.Numerical Example -- 5.6.Convolutive Mixture and Infomax Methods -- 5.6.1.Extensions and Analysis of Algorithms -- 5.6.2.Numerical Example -- 5.7.Relative Sparsity and Time-Frequency Domain Methods -- 5.8.Convex Speech Enhancement Model -- 5.8.1.Convex Model and l1 Regularization -- 5.8.2.Minimization by Bregman Method -- 5.9.Summary and Other Methods for Further Reading -- 5.10.Matlab Programs -- 5.11.Exercises.
9783319030852 (hbk. : alk. paper) 331903085X (hbk. : alk. paper)
40023574930
2012526671
Signal processing--Mathematics.
Signal processing--Mathematics.
TK5102.9 / .X56 2014
006.454 XIN Q.10
Mathematical modeling and signal processing in speech and hearing sciences / Jack Xin, Yingyong Qi. - xi, 206 pages : illustrations ; 24 cm. - MS&A, volume 10 2037-5263 ; . - MS&A (Series) ; v. 10. .
Includes bibliographical references (pages [189]-197) and index.
Machine generated contents note: 1.Background Signal Processing, Statistical and Optimization Methods -- 1.1.Introduction -- 1.2.Fourier and z-Transforms -- 1.2.1.Continuous Time Signals -- 1.2.2.Fourier Transform and Basic Properties -- 1.2.3.Discrete Time Signals and Systems -- 1.2.4.Sampling and Shannon Theory -- 1.2.5.Discrete Fourier Transform -- 1.2.6.Discrete Time and Windowed Fourier Transforms -- 1.2.7.Short Time Fourier Transform, Synthesis and Spectrogram -- 1.2.8.z-Transform -- 1.3.Filtering and Convolution -- 1.3.1.Circular Convolution -- 1.3.2.Linear Convolution and z-Transform -- 1.3.3.Circular Convolution and z-Transform -- 1.3.4.Rational Filters, Impulse and Frequency Responses -- 1.3.5.Group and Phase Delays -- 1.3.6.Minimum Phase and All Pass Filters -- 1.4.Random Variables, Correlation and Independence -- 1.4.1.Basic Notion and Examples -- 1.4.2.Joint Distribution and Independent Components -- 1.4.3.Random Number Generation -- 1.4.4.Stochastic Processes -- 1.4.5.Random Walk and Brownian Motion -- 1.5.Data Clustering and K-Means Method -- 1.6.Maximum Likelihood Method -- 1.7.Least Squares and Sparse Optimization Methods -- 1.8.Exercises -- 2.Speech Modeling -- 2.1.Introduction -- 2.2.Two Mass Vocal Fold Model -- 2.3.Matlab Program and Animation of Two Mass Model -- 2.4.Hydrodynamic Semi-Continuum Vocal Fold Model -- 2.5.Source-Filter Model of Speech Production -- 2.5.1.Uniform Lossless Tube Model and Transfer Function -- 2.5.2.Concatenated Lossless Tube Model: Traveling Waves and Transfer Function -- 2.5.3.Radiation and the Complete Model -- 2.5.4.Matlab Programs for Vowel and Consonant Synthesis -- 2.6.Exercises -- 3.Auditory Modeling -- 3.1.Introduction -- 3.2.Macromechanics and Passive Models -- 3.3.Micromechanics and Two Level Nonlocal Active Models -- 3.4.Dispersion and Decay Properties of Plane Waves -- 3.5.Time Harmonic Solutions -- 3.6.Asymptotic and Transform Techniques -- 3.7.Logarithmic Scales and Critical Bands -- 3.8.Time Demain Method and Dispersive Instability -- 3.9.Boundary Integral Method and Suppression of Instability -- 3.10.Computational Methods of Nonlocal Active Models -- 3.11.Nonlinear Phenomena and Sound Masking -- 3.12.Invertible Auditory Transforms -- 3.13.Orthogonal Auditory Transforms -- 3.14.Modeling Masking Thresholds -- 3.15.Modeling Hearing Loss and Hearing Aids -- 3.16.Matlab Programs -- 3.17.Exercises -- 4.Speech Recognition -- 4.1.Introduction -- 4.2.Hidden Markov Model (HMM) for Speech Processing -- 4.2.1.Speech Spectral Analysis -- 4.2.2.Vector Quantization -- 4.3.HMM for Isolated Word Recognition -- 4.3.1.Forward and Backward Probabilities -- 4.3.2.Baum-Welch Re-Estimation -- 4.3.3.Viterbi Decoding -- 4.4.Summary of Matlab Programs -- 4.5.Chapter Summary -- 4.6.Matlab Programs -- 4.7.Exercises -- 5.Blind Source Separation and Speech Enhancement -- 5.1.Introduction -- 5.2.Instantaneous Mixture and Decorrelation Methods -- 5.2.1.Decorrelation with Second Order Statistics -- 5.2.2.Demixing with Joint Second and Third Order Statistics -- 5.3.Instantaneous Mixture and Cumulant Method -- 5.3.1.Moments and Cumulants -- 5.3.2.Source Recovery and Whitening Process -- 5.3.3.Unitary Factor as Joint Diagonalizer of Cumulant Matrices -- 5.3.4.Joint Diagonalization of Eigenmatrices -- 5.3.5.Jacobi Method and Joint Diagonalizer Formula -- 5.4.Instantaneous Mixture and Infomax Methods -- 5.4.1.Statistical Equations for Source Separation -- 5.4.2.Iterative Methods -- 5.4.3.Uniform Bounds -- 5.4.4.Convergence and Source Separation -- 5.4.5.Numerical Example -- 5.5.Convolutive Mixture and Decorrelation Method -- 5.5.1.Decorrelation Equations -- 5.5.2.Constrained and Penalized Optimization -- 5.5.3.Numerical Example -- 5.6.Convolutive Mixture and Infomax Methods -- 5.6.1.Extensions and Analysis of Algorithms -- 5.6.2.Numerical Example -- 5.7.Relative Sparsity and Time-Frequency Domain Methods -- 5.8.Convex Speech Enhancement Model -- 5.8.1.Convex Model and l1 Regularization -- 5.8.2.Minimization by Bregman Method -- 5.9.Summary and Other Methods for Further Reading -- 5.10.Matlab Programs -- 5.11.Exercises.
9783319030852 (hbk. : alk. paper) 331903085X (hbk. : alk. paper)
40023574930
2012526671
Signal processing--Mathematics.
Signal processing--Mathematics.
TK5102.9 / .X56 2014
006.454 XIN Q.10