TY - JOUR
T1 - Distributed multiple constraints generalized sidelobe canceler for fully connected wireless acoustic sensor networks
AU - Markovich-Golan, Shmulik
AU - Gannot, Sharon
AU - Cohen, Israel
PY - 2013
Y1 - 2013
N2 - This paper proposes a distributed multiple constraints generalized sidelobe canceler (GSC) for speech enhancement in an $N$-node fully connected wireless acoustic sensor network (WASN) comprising M microphones. Our algorithm is designed to operate in reverberant environments with P constrained speakers (including both desired and competing speakers). Rather than broadcasting M microphone signals, a significant communication bandwidth reduction is obtained by performing local beamforming at the nodes, and utilizing only N+P transmission channels. Each node processes its own microphone signals together with the transmitted signals. The GSC-form implementation, by separating the constraints and the minimization, enables the adaptation of the BF during speech-absent time segments, and relaxes the requirement of other distributed LCMV based algorithms to re-estimate the sources RTFs after each iteration. We provide a full convergence proof of the proposed structure to the centralized GSC-beamformer (BF). An extensive experimental study of both narrowband and (wideband) speech signals verifies the theoretical analysis.
AB - This paper proposes a distributed multiple constraints generalized sidelobe canceler (GSC) for speech enhancement in an $N$-node fully connected wireless acoustic sensor network (WASN) comprising M microphones. Our algorithm is designed to operate in reverberant environments with P constrained speakers (including both desired and competing speakers). Rather than broadcasting M microphone signals, a significant communication bandwidth reduction is obtained by performing local beamforming at the nodes, and utilizing only N+P transmission channels. Each node processes its own microphone signals together with the transmitted signals. The GSC-form implementation, by separating the constraints and the minimization, enables the adaptation of the BF during speech-absent time segments, and relaxes the requirement of other distributed LCMV based algorithms to re-estimate the sources RTFs after each iteration. We provide a full convergence proof of the proposed structure to the centralized GSC-beamformer (BF). An extensive experimental study of both narrowband and (wideband) speech signals verifies the theoretical analysis.
KW - Array signal processing
KW - microphone array
KW - speech enhancement
UR - http://www.scopus.com/inward/record.url?scp=84871386194&partnerID=8YFLogxK
U2 - 10.1109/tasl.2012.2224454
DO - 10.1109/tasl.2012.2224454
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AN - SCOPUS:84871386194
SN - 1558-7916
VL - 21
SP - 343
EP - 356
JO - IEEE Transactions on Audio, Speech and Language Processing
JF - IEEE Transactions on Audio, Speech and Language Processing
IS - 2
M1 - 6329934
ER -