TY - JOUR
T1 - A dedicated greedy pursuit algorithm for sparse spectral representation of music sound
AU - Rebollo-Neira, Laura
AU - Aggarwal, Gagan
N1 - © 2016 Acoustical Society of America
PY - 2016/10/28
Y1 - 2016/10/28
N2 - A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to enable the representation of a piece of music signal as a linear superposition of as few spectral components as possible, without affecting the quality of the reproduction. A representation of this nature is said to be sparse. In the present context sparsity is accomplished by greedy selection of the spectral components, from an overcomplete set called a dictionary. The proposed algorithm is tailored to be applied with trigonometric dictionaries. Its distinctive feature being that it avoids the need for the actual construction of the whole dictionary, by implementing the required operations via the fast Fourier transform. The achieved sparsity is theoretically equivalent to that rendered by the orthogonal matching pursuit (OMP) method. The contribution of the proposed dedicated implementation is to extend the applicability of the standard OMP algorithm, by reducing its storage and computational demands. The suitability of the approach for producing sparse spectral representation is illustrated by comparison with the traditional method, in the line of the short time Fourier transform, involving only the corresponding orthonormal trigonometric basis.
AB - A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to enable the representation of a piece of music signal as a linear superposition of as few spectral components as possible, without affecting the quality of the reproduction. A representation of this nature is said to be sparse. In the present context sparsity is accomplished by greedy selection of the spectral components, from an overcomplete set called a dictionary. The proposed algorithm is tailored to be applied with trigonometric dictionaries. Its distinctive feature being that it avoids the need for the actual construction of the whole dictionary, by implementing the required operations via the fast Fourier transform. The achieved sparsity is theoretically equivalent to that rendered by the orthogonal matching pursuit (OMP) method. The contribution of the proposed dedicated implementation is to extend the applicability of the standard OMP algorithm, by reducing its storage and computational demands. The suitability of the approach for producing sparse spectral representation is illustrated by comparison with the traditional method, in the line of the short time Fourier transform, involving only the corresponding orthonormal trigonometric basis.
UR - http://scitation.aip.org/content/asa/journal/jasa/140/4/10.1121/1.4964342
UR - http://www.scopus.com/inward/record.url?scp=84994012344&partnerID=8YFLogxK
U2 - 10.1121/1.4964342
DO - 10.1121/1.4964342
M3 - Article
SN - 0001-4966
VL - 140
SP - 2933
EP - 2943
JO - Journal of the Acoustical Society of America
JF - Journal of the Acoustical Society of America
IS - 4
ER -