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. Fundamentals of Digital Signal Processing for Speech Processing. Sampling Theory. Waveform Coding and Quantization. Differential Coding. Differential Coding Introduction. Linear Predictive Coding (LPC). Vector Quantization for Speech Coding Applications. Analysis-by-Synthesis Coding of Speech. Internet Low Bit-Rate Coder (iLBC). Signal Processing in VoIP Systems. Real-Time DSP Implementation of ITU G.729 Speech Coder. Conclusions and Future Directions for Speech Coding. Summary of Chapters 1-12. Future Directions for Speech. Research. References. Index.
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).