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Successive Approximation Algorithm for LPC Estimation Using Sparse Residual Constraint

Chetupalli, Srikanth Raj and Thippur, Sreenivas (2015) Successive Approximation Algorithm for LPC Estimation Using Sparse Residual Constraint. In: 21st National Conference on Communications (NCC), FEB 27-MAR 01, 2015, Indian Inst Technol, Bombay, INDIA.

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Official URL: http://dx.doi.org/10.1109/NCC.2015.7084883


Estimation of linear prediction coefficients under the sparsity constraint of the prediction residue, is a modification of the traditional minimum mean square error linear predictor formulation, which accounts for the impulse nature of the residual signal for voiced speech signals. This is solved using the 1-norm minimization approach under sparsity constraints. In this paper, we develop a successive approximation algorithm for estimating the linear predictor coefficients and the sparse residual signal. We illustrate the usefulness of the proposed approach using synthetic, and also real speech examples. Experimental results in a multipulse based analysis-synthesis show that the proposed approach can provide better perceptual quality speech reconstruction than the orthogonal matching pursuit based algorithm, with computational time much lower than convex optimization based techniques.

Item Type: Conference Proceedings
Series.: National Conference on Communications NCC
Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 24 Aug 2016 09:35
Last Modified: 24 Aug 2016 09:35
URI: http://eprints.iisc.ac.in/id/eprint/54562

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