Paper Info
Title
Distributed labelling of audio sources in wireless acoustic sensor networks using consensus and matching.
Abstract
In this paper, we propose a new method for distributed labelling of audio sources in wireless acoustic sensor networks (WASNs). We consider WASNs comprising of nodes equipped with multiple microphones observing signals transmitted by multiple sources. An important step toward a cooperation between the nodes, e.g. for a voice-activity-detection, is a network-wide consensus on the source labelling such that all nodes assign the same unique label to each source. In this paper, a hierarchical approach is applied such that first a network clustering algorithm is performed and then in each sub-network, the energy signatures of the sources are estimated using a non-negative independent component analysis over the energy patterns observed by the different nodes. Finally the source labels are obtained by an iterative consensus and matching algorithm, which compares and matches the energy signatures estimated in different sub-networks. The experimental results show the effectiveness of the proposed method.
Year
Venue
Keywords
2016
European Signal Processing Conference
Distributed labelling,consensus and matching,wireless acoustic sensor networks,energy signatures,non-negative independent component analysis
Field
DocType
ISSN
Key distribution in wireless sensor networks,Wireless,Pattern recognition,Computer science,Real-time computing,Acoustic sensor,Independent component analysis,Labelling,Artificial intelligence,Cluster analysis,Wireless sensor network,Blossom algorithm
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Mohamad Hasan Bahari1635.78
Jorge Plata-Chaves21159.92
Alexander Bertrand360748.80
Marc Moonen43673326.91