  Audio compression has become one of the basic multimedia technologies.
Choosing an efficient compression scheme that is capable of preserving the
signal quality while providing a high compression ratio is desirable in the
different standards worldwide. In this paper we study the application of two
highly acclaimed sparse signal processing algorithms, namely, Compressed
Sensing (CS) and Sparse Fart Fourier transform, to audio compression. In
addition, we present a Sparse Fast Fourier transform (SFFT)-based framework to
compress audio signal. This scheme embeds the K-largest frequencies indices as
part of the transmitted signal and thus saves in the bandwidth required for
transmission
