Compressive sampling and adaptive dictionary learning for the packet loss recovery in audio multimedia streaming

Abstract

In this work, a scheme based on a compressive sampling technique and a fast dictionary learning approach for reconstructing audio content in multimedia streaming is introduced. Audio streaming data are encapsulated in different packets by means of an interleaving technique. The compressive sampling technique is used to reconstruct audio information in case of lost packets, with a sparsifying basis provided by a greedy adaptive dictionary learning algorithm. In order to assess the performance of the methodology, several experiments on speech and musical audio signals are presented.