Principles of Speech Coding

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

• 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.