LEADER 01251nam--2200397---450- 001 990001539930203316 005 20041222171431.0 035 $a000153993 035 $aUSA01000153993 035 $a(ALEPH)000153993USA01 035 $a000153993 100 $a20040326d1986----km-y0itay0103----ba 101 0 $aita 102 $aIT 105 $a||||||||001yy 200 1 $a<> savio e il ribelle$eManzoni e Leopardi$fUgo Dotti 210 $aRoma$cEditori Riuniti$d1986 215 $a174 p.$d21 cm. 225 2 $aNuova biblioteca di cultura$v268 410 0$12001$aNuova biblioteca di cultura$v268 454 1$12001 461 1$1001-------$12001 600 $aManzoni,$bAlessandro$xOpere$xCritica 600 $aLeopardi,$bGiacomo$xOpere$xCritica 700 1$aDOTTI,$bUgo$0131604 801 0$aIT$bsalbc$gISBD 912 $a990001539930203316 951 $aVI.3.B. 170(Varie coll. 15/268)$b16689/86 L.M.$cVarie coll. 951 $aVI.3.B. 170a(Varie coll. 15/268 bis)$b16690/86 L.M.$cVarie coll. 959 $aBK 969 $aUMA 979 $aSIAV8$b10$c20040326$lUSA01$h1356 979 $aPATRY$b90$c20040406$lUSA01$h1747 979 $aCOPAT2$b90$c20041222$lUSA01$h1714 996 $aSavio e il ribelle$9148203 997 $aUNISA LEADER 10649nam 22004813 450 001 9910829806303321 005 20231121080239.0 010 $a1-119-06099-0 010 $a1-119-06097-4 035 $a(CKB)4330000000008247 035 $a(MiAaPQ)EBC30954506 035 $a(Au-PeEL)EBL30954506 035 $a(EXLCZ)994330000000008247 100 $a20231121d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDigital Speech Transmission and Enhancement 205 $a2nd ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2023. 210 4$dİ2024. 215 $a1 online resource (595 pages) 225 1 $aIEEE Press Series 311 $a1-119-06096-6 327 $aCover -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1 Introduction -- Chapter 2 Models of Speech Production and Hearing -- 2.1 Sound Waves -- 2.2 Organs of Speech Production -- 2.3 Characteristics of Speech Signals -- 2.4 Model of Speech Production -- 2.4.1 Acoustic Tube Model of the Vocal Tract -- 2.4.2 Discrete Time All?Pole Model of the Vocal Tract -- 2.5 Anatomy of Hearing -- 2.6 Psychoacoustic Properties of the Auditory System -- 2.6.1 Hearing and Loudness -- 2.6.2 Spectral Resolution -- 2.6.3 Masking -- 2.6.4 Spatial Hearing -- 2.6.4.1 Head?Related Impulse Responses and Transfer Functions -- 2.6.4.2 Law of The First Wavefront -- References -- Chapter 3 Spectral Transformations -- 3.1 Fourier Transform of Continuous Signals -- 3.2 Fourier Transform of Discrete Signals -- 3.3 Linear Shift Invariant Systems -- 3.3.1 Frequency Response of LSI Systems -- 3.4 The z?transform -- 3.4.1 Relation to Fourier Transform -- 3.4.2 Properties of the ROC -- 3.4.3 Inverse z?Transform -- 3.4.4 z?Transform Analysis of LSI Systems -- 3.5 The Discrete Fourier Transform -- 3.5.1 Linear and Cyclic Convolution -- 3.5.2 The DFT of Windowed Sequences -- 3.5.3 Spectral Resolution and Zero Padding -- 3.5.4 The Spectrogram -- 3.5.5 Fast Computation of the DFT: The FFT -- 3.5.6 Radix?2 Decimation?in?Time FFT -- 3.6 Fast Convolution -- 3.6.1 Fast Convolution of Long Sequences -- 3.6.2 Fast Convolution by Overlap?Add -- 3.6.3 Fast Convolution by Overlap?Save -- 3.7 Analysis-Modification-Synthesis Systems -- 3.8 Cepstral Analysis -- 3.8.1 Complex Cepstrum -- 3.8.2 Real Cepstrum -- 3.8.3 Applications of the Cepstrum -- 3.8.3.1 Construction of Minimum?Phase Sequences -- 3.8.3.2 Deconvolution by Cepstral Mean Subtraction -- 3.8.3.3 Computation of the Spectral Distortion Measure -- 3.8.3.4 Fundamental Frequency Estimation -- References. 327 $aChapter 4 Filter Banks for Spectral Analysis and Synthesis -- 4.1 Spectral Analysis Using Narrowband Filters -- 4.1.1 Short?Term Spectral Analyzer -- 4.1.2 Prototype Filter Design for the Analysis Filter Bank -- 4.1.3 Short?Term Spectral Synthesizer -- 4.1.4 Short?Term Spectral Analysis and Synthesis -- 4.1.5 Prototype Filter Design for the Analysis-Synthesis filter bank -- 4.1.6 Filter Bank Interpretation of the DFT -- 4.2 Polyphase Network Filter Banks -- 4.2.1 PPN Analysis Filter Bank -- 4.2.2 PPN Synthesis Filter Bank -- 4.3 Quadrature Mirror Filter Banks -- 4.3.1 Analysis-Synthesis Filter Bank -- 4.3.2 Compensation of Aliasing and Signal Reconstruction -- 4.3.3 Efficient Implementation -- 4.4 Filter Bank Equalizer -- 4.4.1 The Reference Filter Bank -- 4.4.2 Uniform Frequency Resolution -- 4.4.3 Adaptive Filter Bank Equalizer: Gain Computation -- 4.4.3.1 Conventional Spectral Subtraction -- 4.4.3.2 Filter Bank Equalizer -- 4.4.4 Non?uniform Frequency Resolution -- 4.4.5 Design Aspects & -- Implementation -- References -- Chapter 5 Stochastic Signals and Estimation -- 5.1 Basic Concepts -- 5.1.1 Random Events and Probability -- 5.1.2 Conditional Probabilities -- 5.1.3 Random Variables -- 5.1.4 Probability Distributions and Probability Density Functions -- 5.1.5 Conditional PDFs -- 5.2 Expectations and Moments -- 5.2.1 Conditional Expectations and Moments -- 5.2.2 Examples -- 5.2.2.1 The Uniform Distribution -- 5.2.2.2 The Gaussian Density -- 5.2.2.3 The Exponential Density -- 5.2.2.4 The Laplace Density -- 5.2.2.5 The Gamma Density -- 5.2.2.6 ?2?Distribution -- 5.2.3 Transformation of a Random Variable -- 5.2.4 Relative Frequencies and Histograms -- 5.3 Bivariate Statistics -- 5.3.1 Marginal Densities -- 5.3.2 Expectations and Moments -- 5.3.3 Uncorrelatedness and Statistical Independence -- 5.3.4 Examples of Bivariate PDFs. 327 $a5.3.4.1 The Bivariate Uniform Density -- 5.3.4.2 The Bivariate Gaussian Density -- 5.3.5 Functions of Two Random Variables -- 5.4 Probability and Information -- 5.4.1 Entropy -- 5.4.2 Kullback-Leibler Divergence -- 5.4.3 Cross?Entropy -- 5.4.4 Mutual Information -- 5.5 Multivariate Statistics -- 5.5.1 Multivariate Gaussian Distribution -- 5.5.2 Gaussian Mixture Models -- 5.6 Stochastic Processes -- 5.6.1 Stationary Processes -- 5.6.2 Auto?Correlation and Auto?Covariance Functions -- 5.6.3 Cross?Correlation and Cross?Covariance Functions -- 5.6.4 Markov Processes -- 5.6.5 Multivariate Stochastic Processes -- 5.7 Estimation of Statistical Quantities by Time Averages -- 5.7.1 Ergodic Processes -- 5.7.2 Short?Time Stationary Processes -- 5.8 Power Spectrum and its Estimation -- 5.8.1 White Noise -- 5.8.2 The Periodogram -- 5.8.3 Smoothed Periodograms -- 5.8.3.1 Non Recursive Smoothing in Time -- 5.8.3.2 Recursive Smoothing in Time -- 5.8.3.3 Log?Mel Filter Bank Features -- 5.8.4 Power Spectra and Linear Shift?Invariant Systems -- 5.9 Statistical Properties of Speech Signals -- 5.10 Statistical Properties of DFT Coefficients -- 5.10.1 Asymptotic Statistical Properties -- 5.10.2 Signal?Plus?Noise Model -- 5.10.3 Statistics of DFT Coefficients for Finite Frame Lengths -- 5.11 Optimal Estimation -- 5.11.1 MMSE Estimation -- 5.11.2 Estimation of Discrete Random Variables -- 5.11.3 Optimal Linear Estimator -- 5.11.4 The Gaussian Case -- 5.11.5 Joint Detection and Estimation -- 5.12 Non?Linear Estimation with Deep Neural Networks -- 5.12.1 Basic Network Components -- 5.12.1.1 The Perceptron -- 5.12.1.2 Convolutional Neural Network -- 5.12.2 Basic DNN Structures -- 5.12.2.1 Fully?Connected Feed?Forward Network -- 5.12.2.2 Autoencoder Networks -- 5.12.2.3 Recurrent Neural Networks -- 5.12.2.4 Time Delay, Wavenet, and Transformer Networks. 327 $a5.12.2.5 Training of Neural Networks -- 5.12.2.6 Stochastic Gradient Descent (SGD) -- 5.12.2.7 Adaptive Moment Estimation Method (ADAM) -- References -- Chapter 6 Linear Prediction -- 6.1 Vocal Tract Models and Short?Term Prediction -- 6.1.1 All?Zero Model -- 6.1.2 All?Pole Model -- 6.1.3 Pole?Zero Model -- 6.2 Optimal Prediction Coefficients for Stationary Signals -- 6.2.1 Optimum Prediction -- 6.2.2 Spectral Flatness Measure -- 6.3 Predictor Adaptation -- 6.3.1 Block?Oriented Adaptation -- 6.3.1.1 Auto?Correlation Method -- 6.3.1.2 Covariance Method -- 6.3.1.3 Levinson-Durbin Algorithm -- 6.3.2 Sequential Adaptation -- 6.4 Long?Term Prediction -- References -- Chapter 7 Quantization -- 7.1 Analog Samples and Digital Representation -- 7.2 Uniform Quantization -- 7.3 Non?uniform Quantization -- 7.4 Optimal Quantization -- 7.5 Adaptive Quantization -- 7.6 Vector Quantization -- 7.6.1 Principle -- 7.6.2 The Complexity Problem -- 7.6.3 Lattice Quantization -- 7.6.4 Design of Optimal Vector Code Books -- 7.6.5 Gain-Shape Vector Quantization -- 7.7 Quantization of the Predictor Coefficients -- 7.7.1 Scalar Quantization of the LPC Coefficients -- 7.7.2 Scalar Quantization of the Reflection Coefficients -- 7.7.3 Scalar Quantization of the LSF Coefficients -- References -- Chapter 8 Speech Coding -- 8.1 Speech?Coding Categories -- 8.2 Model?Based Predictive Coding -- 8.3 Linear Predictive Waveform Coding -- 8.3.1 First?Order DPCM -- 8.3.2 Open?Loop and Closed?Loop Prediction -- 8.3.3 Quantization of the Residual Signal -- 8.3.3.1 Quantization with Open?Loop Prediction -- 8.3.3.2 Quantization with Closed?Loop Prediction -- 8.3.3.3 Spectral Shaping of the Quantization Error -- 8.3.4 ADPCM with Sequential Adaptation -- 8.4 Parametric Coding -- 8.4.1 Vocoder Structures -- 8.4.2 LPC Vocoder -- 8.5 Hybrid Coding -- 8.5.1 Basic Codec Concepts. 327 $a8.5.1.1 Scalar Quantization of the Residual Signal -- 8.5.1.2 Vector Quantization of the Residual Signal -- 8.5.2 Residual Signal Coding: RELP -- 8.5.3 Analysis by Synthesis: CELP -- 8.5.3.1 Principle -- 8.5.3.2 Fixed Code Book -- 8.5.3.3 Long?Term Prediction, Adaptive Code Book -- 8.6 Adaptive Postfiltering -- 8.7 Speech Codec Standards: Selected Examples -- 8.7.1 GSM Full?Rate Codec -- 8.7.2 EFR Codec -- 8.7.3 Adaptive Multi?Rate Narrowband Codec (AMR?NB) -- 8.7.4 ITU?T/G.722: 7?kHz Audio Coding within 64 kbit/s -- 8.7.5 Adaptive Multi?Rate Wideband Codec (AMR?WB) -- 8.7.6 Codec for Enhanced Voice Services (EVS) -- 8.7.7 Opus Codec IETF RFC 6716 -- References -- Chapter 9 Concealment of Erroneous or Lost Frames -- 9.1 Concepts for Error Concealment -- 9.1.1 Error Concealment by Hard Decision Decoding -- 9.1.2 Error Concealment by Soft Decision Decoding -- 9.1.3 Parameter Estimation -- 9.1.3.1 MAP Estimation -- 9.1.3.2 MS Estimation -- 9.1.4 The A Posteriori Probabilities -- 9.1.4.1 The A Priori Knowledge -- 9.1.4.2 The Parameter Distortion Probabilities -- 9.1.5 Example: Hard Decision vs. Soft Decision -- 9.2 Examples of Error Concealment Standards -- 9.2.1 Substitution and Muting of Lost Frames -- 9.2.2 AMR Codec: Substitution and Muting of Lost Frames -- 9.2.3 EVS Codec: Concealment of Lost Packets -- 9.3 Further Improvements -- References -- Chapter 10 Bandwidth Extension of Speech Signals -- 10.1 BWE Concepts -- 10.2 BWE using the Model of Speech Production -- 10.2.1 Extension of the Excitation Signal -- 10.2.2 Spectral Envelope Estimation -- 10.2.2.1 Minimum Mean Square Error Estimation -- 10.2.2.2 Conditional Maximum A Posteriori Estimation -- 10.2.2.3 Extensions -- 10.2.2.4 Simplifications -- 10.2.3 Energy Envelope Estimation -- 10.3 Speech Codecs with Integrated BWE -- 10.3.1 BWE in the GSM Full?Rate Codec. 327 $a10.3.2 BWE in the AMR Wideband Codec. 410 0$aIEEE Press Series 676 $a006.454 700 $aVary$b Peter$01646621 701 $aMartin$b Rainer$0353494 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910829806303321 996 $aDigital Speech Transmission and Enhancement$94112952 997 $aUNINA