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On compressed sensing and its application to speech and audio signals

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3 Author(s)
Mads Græsbøll Christensen ; Dept. of Media Technology, Aalborg University, Denmark ; Jan Østergaard ; Søren Holdt Jensen

In this paper, we consider the application of compressed sensing (aka compressive sampling) to speech and audio signals. We discuss the design considerations and issues that must be addressed in doing so, and we apply compressed sensing as a pre-processor to sparse decompositions of real speech and audio signals using dictionaries composed of windowed complex sinusoids. Our results demonstrate that the principles of compressed sensing can be applied to sparse decompositions of speech and audio signals and that it offers a significant reduction of the computational complexity, but also that such signals may pose a challenge due to their non-stationary and complex nature with varying levels of sparsity.

Published in:

2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers

Date of Conference:

1-4 Nov. 2009