Abstract
This paper discusses major digital signal processing methods used in processing speech signals. Basic tools, such as the discrete Fourier transform, the z transform and linear filter theory are briefly introduced first. A general view of fast transformation algorithms and most widely used particular fast transformations are given. Linear prediction is then described with a particular emphasis on its lattice structure. A brief introduction to homomorphic processing for multiplied and convolved signals and to its applications in speech processing is given. Recalling some fundamentals of the speech signal, various speech analysis and synthesis models are described, showing which kind of processing methods are involved. Finally, two aspects of speech recognition are presented: feature traction and pattern matching using dynamic time warping.
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