Signal Processing Fundamentals

  • Priyabrata Sinha


The first stepping stone to understanding the concepts and applications of Speech Processing is to be familiar with the fundamental principles of digital signal processing. Since all real-world signals are essentially analog, these must be converted into a digital format suitable for computations on a microprocessor. Sampling the signal and quantizing it into suitable digital values are critical considerations in being able to represent the signal accurately. Processing the signal often involves evaluating the effect of a predesigned system, which is accomplished using mathematical operations such as convolution. It also requires understanding the similarity or other relationship between two signals, through operations like autocorrelation and cross-correlation. Often, the frequency content of the signal is the parameter of primary importance, and in many cases this frequency content is manipulated through signal filtering techniques. This chapter will explore many of these foundational signal processing techniques and considerations, as well as the algorithmic structures that enable such processing.


Fast Fourier Transform Impulse Response Speech Signal Discrete Fourier Transform Finite Impulse Response 
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    Rabiner LR, Schafer RW Digital processing of speech signals, Prentice Hall, 1998.Google Scholar
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    Chau WC Speech coding algorithms, CRC Press, 2001.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Microchip Technology, Inc.ChandlerUSA

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