Principles of Speech Coding: 1st Edition (Hardback) book cover

Principles of Speech Coding

1st Edition

By Tokunbo Ogunfunmi, Madihally Narasimha

CRC Press

381 pages | 186 B/W Illus.

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pub: 2010-04-29
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It is becoming increasingly apparent that all forms of communication—including voice—will be transmitted through packet-switched networks based on the Internet Protocol (IP). Therefore, the design of modern devices that rely on speech interfaces, such as cell phones and PDAs, requires a complete and up-to-date understanding of the basics of speech coding.

Outlines key signal processing algorithms used to mitigate impairments to speech quality in VoIP networks

Offering a detailed yet easily accessible introduction to the field, Principles of Speech Coding provides an in-depth examination of the underlying signal processing techniques used in speech coding. The authors present coding standards from various organizations, including the International Telecommunication Union (ITU). With a focus on applications such as Voice-over-IP telephony, this comprehensive text covers recent research findings on topics including:

  • A general introduction to speech processing
  • Digital signal processing concepts
  • Sampling theory and related topics
  • Principles of pulse code modulation (PCM) and adaptive differential pulse code modulation (ADPCM) standards
  • Linear prediction (LP) and use of the linear predictive coding (LPC) model
  • Vector quantization and its applications in speech coding
  • Case studies of practical speech coders from ITU and others
  • The Internet low-bit-rate coder (ILBC)

Developed from the authors’ combined teachings, this book also illustrates its contents by providing a real-time implementation of a speech coder on a digital signal processing chip. With its balance of theory and practical coverage, it is ideal for senior-level undergraduate and graduate students in electrical and computer engineering. It is also suitable for engineers and researchers designing or using speech coding systems in their work.

Table of Contents

Introduction to Speech Coding

Speech Signals

Characteristics of Speech Signals

Modeling of Speech

Speech Analysis

Speech Coding

Varieties of Speech Coders

Measuring Speech Quality

Communication Networks and Speech Coding

Performance Issues in Speech Communication Systems

Summary of Speech Coding Standards

Fundamentals of DSP for Speech Processing

Introduction to LTI Systems

Review of Digital Signal Processing

Review of Stochastic Signal Processing

Response of a Linear System to a Stochastic Process Input


AR Models for Speech Signals, Yule–Walker Equations

Short-Term Frequency (or Fourier) Transform and Cepstrum Periodograms

Spectral Envelope Determination for Speech Signals

Voiced/Unvoiced Classification of Speech Signals

Pitch Period Estimation Methods

Sampling Theory

Nyquist Sampling Theorem

Reconstruction of the Original Signal: Interpolation Filters

Practical Reconstruction

Aliasing and In-Band Distortion

Effect of Sampling Clock Jitter

Sampling and Reconstruction of Random Signals

Waveform Coding and Quantization


Quantizer Performance Evaluation

Quantizer Transfer Function

Quantizer Performance under No-Overload Conditions

Uniform Quantizer

Nonuniform Quantizer

Logarithmic Companding

Segmented Companding Laws

ITU G.711 μ-Law and A-Law PCM Standards

Optimum Quantization

Adaptive Quantization

Differential Coding

Closed-Loop Differential Quantizer

Generalization to Predictive Coding

ITU G.726 ADPCM Algorithm

Linear Deltamodulation

Adaptive Deltamodulation

Linear Prediction

Properties of the Autocorrelation Matrix, R 136

Relation between Linear Prediction and AR Modeling

Augmented Wiener Hopf Equations for Forward Prediction

Backward Prediction-Error Filter

Augmented Wiener Hopf Equations for Backward Prediction

LD Recursion

Linear Predictive Coding

Linear Predictive Coding

LPC-10 Federal Standard

Introduction to CELP-Based Coders

Vector Quantization for Speech Coding Applications

Review of Scalar Quantization

Vector Quantization

Lloyd’s Algorithm for Vector Quantizer Design

The Linde–Buzo–Gray Algorithm

Popular Search Algorithms for VQ Quantizer Design

Other Suboptimal Algorithms for VQ Quantizer Design

Applications in Standards

Analysis-by-Synthesis Coding of Speech

CELP AbS Structure

Case Study Example: FS 1016 CELP Coder

Case Study Example: ITU-T G.729/729A Speech Coder

Internet Low-Bit-Rate Coder

Internet Low-Bit-Rate Codec .242

iLBC’s Encoding Process 245

iLBC’s Decoding Process 250

iLBC’s PLC Techniques 253

iLBC’s Enhancement Techniques 254

iLBC’s Synthesis and Postfiltering 257

MATLAB’s Signal Processing Blockset iLBC Demo Model


Evolution from PSQM/PSQM + TO PESQ

PESQ Algorithm

PESQ Applications

Signal Processing in VoIP Systems

PSTN and VoIP Networks

Effect of Delay on the Perceived Speech Quality

Line ECANs

Acoustic ECANs

Jitter Buffers

Clock Skew

Packet Loss Recovery Methods

Real-Time DSP Implementation of ITU-T G.729/A Speech Coder

ITU-T G.729/A Speech Coding Standard

TI TMS320C6X DSP Processors

TI’s RF and DSP Algorithm Standard

G.729/A on RF3 on the TI C6X DSP

Running the RF3 Example on EVM

RF3 Resource Requirements

Details of Our Implementation

Migrating ITU-T G.729/A to RF3 and the EVM

Optimizing G.729/A for Real-Time Execution on the EVM

Real-Time Performance for Two Channels

Checking the Test Vectors on the EVM

Going Beyond a Two-Channel Implementation

Conclusions and Future Directions for Speech Coding


Future Directions for Speech Research



About the Authors

Tokunbo Ogunfunmi is a professor in the department of electrical engineering and Director of the Signal Processing Research Lab. (SPRL) at Santa Clara University, California. His research interests include digital adaptive/nonlinear signal processing, speech and video signal processing, artificial neural networks and VLSI design. He has published two books and over 100 refereed journal and conference papers in these and related application areas. Dr. Ogunfunmi has been a consultant to industry and government and a visiting professor at Stanford University and The University of Texas. He is a Senior Member of the Institution of Electrical and Electronic Engineers (IEEE), a Member of Sigma Xi (the Scientific Research Society) , and Member of the American Association for the Advancement of Science (AAAS). He serves as the Chair of the IEEE Signal Processing Society (SPS) Santa Clara Valley Chapter and as a member of several IEEE Technical Committees (TC). He is also a registered professional engineer.

Madihally (Sim) Narasimha is currently a Senior Director of Technology at Qualcomm Inc. Prior to joining Qualcomm, he was Vice President of Technology at Ample Communications, where he directed the development of Ethernet physical layer chips. Prior to that, he served in technology leadership roles at several Voice-over-IP (VoIP) startup companies including IP Unity, Realchip Communications, and Empowertel Networks. He also held senior management positions at Symmetricom and Granger Associates (a subsidiary of DSC Communications Corporation), where he was instrumental in bringing many DSP-based telecommunications products to market. Dr. Narasimha is also a Consulting Professor in the Department of Electrical Engineering at Stanford University, Stanford, CA, where he teaches telecommunications courses and performs research in related areas.He is a Fellow of the Institution of Electrical and Electronic Engineers (IEEE).

Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Computer Graphics
TECHNOLOGY & ENGINEERING / Telecommunications