Digital Audio Signal Processing

Digital Audio Signal Processing The fully revised new edition of the popular textbook, featuring additional MATLAB exercises and new algorithms for processing digital audio signals Digital Audio Signal Processing (DASP) techniques are used in a variety of applications, ranging from audio streaming and computer-generated music to real-time signal processing and virtual sound processing. Digital Audio Signal Processing provides clear and accessible coverage of the fundamental principles and practical applications of digital audio processing and coding. Throughout the book, the authors explain a wide range of basic audio processing techniques and highlight new directions for automatic tuning of different algorithms and discuss state- of-the-art DASP approaches. Now in its third edition, this popular guide is fully updated with the latest signal processing algorithms for audio processing. Entirely new chapters cover nonlinear processing, Machine Learning (ML) for audio applications, distortion, soft/hard clipping, overdrive, equalizers and delay effects, sampling and reconstruction, and more. Covers the fundamentals of quantization, filters, dynamic range control, room simulation, sampling rate conversion, and audio coding Describes DASP techniques, their theoretical foundations, and their practical applications Discusses modern studio technology, digital transmission systems, storage media, and home entertainment audio components Features a new introductory chapter and extensively revised content throughout Provides updated application examples and computer-based activities supported with MATLAB exercises and interactive JavaScript applets via an author-hosted companion website Balancing essential concepts and technological topics, Digital Audio Signal Processing, Third Edition remains the ideal textbook for advanced music technology and engineering students in audio signal processing courses. It is also an invaluable reference for audio engineers, hardware and software developers, and researchers in both academia and industry. Cover Title Page Copyright Contents Preface for the Third Edition Preface for the Second Edition Preface for the First Edition Chapter 1 Introduction 1.1 Continuous‐time Signals and Convolution 1.2 Continuous‐time Fourier Transform and Laplace Transform 1.3 Sampling and Reconstruction 1.4 Discrete‐time Signals and Convolution 1.5 Discrete‐time Fourier Transform and Z‐Transform 1.6 Discrete Fourier Transform 1.7 FIR and IIR Filters 1.8 Adaptive Filters 1.9 Exercises 1.9 References Chapter 2 Quantization 2.1 Signal Quantization 2.1.1 Classical Quantization Model 2.1.2 Quantization Theorem 2.1.3 Statistics of Quantization Error 2.2 Dither 2.2.1 Basics 2.2.2 Implementation 2.2.3 Examples 2.3 Spectrum Shaping of Quantization – Noise Shaping 2.4 Number Representation 2.4.1 Fixed‐point Number Representation 2.4.2 Floating‐point Number Representation 2.4.3 Effects on Format Conversion and Algorithms 2.5 JS Applet – Quantization, Dither, and Noise Shaping 2.6 Exercises 2.6 References Chapter 3 Sampling Rate Conversion 3.1 Basics 3.1.1 Upsampling and Anti‐Imaging Filtering 3.1.2 Downsampling and Antialiasing Filtering 3.2 Synchronous Conversion 3.3 Asynchronous Conversion 3.3.1 Single‐stage Methods 3.3.2 Multistage Methods 3.3.3 Control of Interpolation Filters 3.4 Interpolation Methods 3.4.1 Polynomial Interpolation 3.4.2 Lagrange Interpolation 3.4.3 Spline Interpolation 3.5 Exercises 3.5 References Chapter 4 AD/DA Conversion 4.1 Methods 4.1.1 Nyquist Sampling 4.1.2 Oversampling 4.1.3 Delta‐sigma Modulation 4.2 AD Converters 4.2.1 Specifications 4.2.2 Parallel Converter 4.2.3 Successive Approximation 4.2.4 Counter Methods 4.2.5 Delta‐sigma AD Converter 4.3 DA Converters 4.3.1 Specifications 4.3.2 Switched Voltage and Current Sources 4.3.3 Weighted Resistors and Capacitors 4.3.4 R–2R Resistor Networks 4.3.5 Delta‐sigma DA Converter 4.4 JS Applet – Oversampling and Quantization 4.5 Exercises 4.5 References Chapter 5 Audio Processing Systems 5.1 Digital Signal Processors 5.1.1 Fixed‐point DSPs 5.1.2 Floating‐point DSPs 5.2 Digital Audio Interfaces 5.2.1 Two‐channel AES/EBU Interface 5.2.2 MADI Interface 5.2.3 Audio in HDMI 5.2.4 Audio Computer Interfaces 5.2.5 Audio Network Interfaces 5.3 Two‐channel Systems 5.4 Multi‐channel Systems 5.4 References Chapter 6 Equalizers 6.1 Basics 6.2 Recursive Audio Filters 6.2.1 Design 6.2.2 Parametric Filter Structures 6.2.3 Quantization Effects 6.3 Non‐recursive Audio Filters 6.3.1 Basics of Fast Convolution 6.3.2 Fast Convolution of Long Sequences 6.3.3 Filter Design by Frequency Sampling 6.4 Multi‐complementary Filter Bank 6.4.1 Principles 6.4.2 Example: Eight‐band Multi‐complementary Filter Bank 6.5 Delay‐based Audio Effects 6.6 JS Applet – Audio Filters 6.7 Exercises 6.7 References Chapter 7 Room Simulation 7.1 Basics 7.1.1 Room Acoustics 7.1.2 Model‐based Room Impulse Responses 7.1.3 Measurement of Room Impulse Responses 7.1.4 Simulation of Room Impulse Responses 7.2 Early Reflections 7.2.1 Ando's Investigations 7.2.2 Gerzon Algorithm 7.3 Subsequent Reverberation 7.3.1 Schroeder Algorithm 7.3.2 General Feedback Systems 7.3.3 Feedback Allpass Systems 7.4 Approximation of Room Impulse Responses 7.5 JS Applet – Fast Convolution 7.6 Exercises 7.6 References Chapter 8 Dynamic Range Control 8.1 Basics 8.2 Static Curve 8.3 Dynamic Behavior 8.3.1 Level Measurement 8.3.2 Gain Factor Smoothing 8.3.3 Time Constants 8.4 Implementation 8.4.1 Limiter 8.4.2 Compressor 8.4.3 Compressor, Expander, Noise Gate 8.4.4 Combination System 8.5 Realization Aspects 8.5.1 Sampling Rate Reduction 8.5.2 Curve Approximation 8.5.3 Stereo Processing 8.6 Multiband DRC 8.7 Dynamic Equalizers 8.8 Source‐filter DRC 8.8.1 Introduction 8.8.2 Combination with DRC 8.8.3 Applications 8.9 JS Applet – Dynamic Range Control 8.10 Exercises 8.10 References Chapter 9 Audio Coding 9.1 Lossless Audio Coding 9.2 Lossy Audio Coding 9.3 Psychoacoustics 9.3.1 Critical Bands and Absolute Threshold 9.3.2 Masking 9.4 ISO‐MPEG1 Audio Coding 9.4.1 Filter Banks 9.4.2 Psychoacoustic Models 9.4.3 Dynamic Bit Allocation and Coding 9.5 MPEG‐2 Audio Coding 9.6 MPEG‐2 Advanced Audio Coding 9.7 MPEG‐4 Audio Coding 9.8 Spectral Band Replication 9.9 Constrained Energy Lapped Transform – Gain and Shape Coding 9.9.1 Gain Quantization 9.9.2 Shape Quantization 9.9.3 Range Coding 9.9.4 CELT Decoding 9.10 JS Applet – Psychoacoustics 9.11 Exercises 9.11 References Chapter 10 Nonlinear Processing 10.1 Fundamentals 10.2 Overdrive, Distortion, Clipping 10.3 Nonlinear Filters 10.4 Aliasing and its Mitigation 10.5 Virtual Analog Modeling 10.5.1 Wave Digital Filters 10.5.2 State‐space Approaches 10.6 Exercises 10.6 References Chapter 11 Machine Learning for Audio 11.1 Introduction 11.2 Unsupervised and Supervised Learning 11.3 Gradient Descent and Backpropagation 11.3.1 Feedforward Artificial Neural Network 11.3.2 Convolutional Neural Network 11.4 Applications 11.4.1 Parametric Filter Adaptation 11.4.2 Room Simulation 11.4.3 Audio Denoising 11.5 Exercises 11.5 References Index EULA "The fully revised new edition of the popular textbook, featuring additional MATLAB exercises and new algorithms for processing digital audio signals Digital Audio Signal Processing (DASP) techniques are used in a variety of applications, ranging from audio streaming and computer-generated music to real-time signal processing and virtual sound processing. Digital Audio Signal Processing provides clear and accessible coverage of the fundamental principles and practical applications of digital audio processing and coding. Throughout the book, the authors explain a wide range of basic audio processing techniques and highlight new directions for automatic tuning of different algorithms and discuss state-of-the-art DASP approaches. Now in its third edition, this popular guide is fully updated with the latest signal processing algorithms for audio processing. Entirely new chapters cover nonlinear processing, Machine Learning (ML) for audio applications, distortion, soft/hard clipping, overdrive, equalizers and delay effects, sampling and reconstruction, and more. Covers the fundamentals of quantization, filters, dynamic range control, room simulation, sampling rate conversion, and audio coding Describes DASP techniques, their theoretical foundations, and their practical applications Discusses modern studio technology, digital transmission systems, storage media, and home entertainment audio components Features a new introductory chapter and extensively revised content throughout Provides updated application examples and computer-based activities supported with MATLAB exercises and interactive JavaScript applets via a companion website Balancing essential concepts and technological topics, Digital Audio Signal Processing, Third Edition remains the ideal textbook for advanced music technology and engineering students in audio signal processing courses. It is also an invaluable reference for audio engineers, hardware and software developers, and researchers in both academia and industry"-- Provided by publisher.