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Lecture Notes in Computer Science
Classical digital speech signal processing assumes linearity, timeinvariance, and Gaussian random variables (LTI-Gaussian theory). In this article, we address the suitability of these mathematical assumptions for realistic speech signals with respect to the biophysics of voice production, finding that the LTI-Gaussian approach has some important accuracy and computational efficiency shortcomings in both theory and practice. Next, we explore the consequences of relaxing the assumptions ofdoi:10.1007/978-3-642-25020-0_2 fatcat:rrfe2fyjwjaxxpapgcccoej5la