Title
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.
Year
DOI
Venue
2016
10.1007/s11042-015-3002-x
Multimedia Tools Appl.
Keywords
Field
DocType
Compressive sampling, Dictionary learning, Multimedia streaming, Interleaving
Audio signal,Dictionary learning,Computer science,Network packet,Packet loss,Speech recognition,Software,Multimedia,Interleaving,Compressed sensing,Audio over Ethernet
Journal
Volume
Issue
ISSN
75
24
1573-7721
Citations 
PageRank 
References 
1
0.35
12
Authors
3
Name
Order
Citations
PageRank
Angelo Ciaramella111120.09
marco gianfico210.35
Giulio Giunta316213.35