Title
Source Enumeration And Robust Voice Activity Detection In Wireless Acoustic Sensor Networks
Abstract
We propose a robust technique for multi-speaker voice activity detection and source enumeration in wireless acoustic sensor networks (WASN). The proposed technique first clusters the nodes that observe a single speaker as dominant source, and then estimates the voice activity of each speaker by introducing a block-sparsity penalizing term in the unmixing problem. The method is scalable in terms of the number of simultaneously active speakers, does not require setting empirical thresholds, and is robust to impulsive noise sources. The results are validated using a WASN with four human speakers and two impulsive noise sources observed by 15 nodes.
Year
DOI
Venue
2019
10.1109/IEEECONF44664.2019.9048954
CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS
Keywords
DocType
ISSN
Group-sparse penalization, multiplicative non-negative ICA, node clustering, source enumeration, voice activity detection, wireless acoustic sensor network
Conference
1058-6393
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Tanuj Hasija1102.36
Martin Golz24610.68
Michael Muma314419.51
Peter J. Schreier431732.69
Abdelhak M. Zoubir51036148.03