TY - GEN
T1 - Performance enhancement of SSC sound source localization for indoor environment
AU - Yuan, Xiaokun
AU - Cai, De
AU - Deng, Jiahao
AU - Li, Ping
AU - Gong, Peng
PY - 2012
Y1 - 2012
N2 - The steered response power-phase transform algorithm (SRP-PHAT) has been widely utilized for robust sound source localization for indoor environment. Searching space clustering algorithm (SSC) is the improved version of SRP-PHAT, in which the computational complexity could be greatly reduced via the space division and clustering. However, SSC has to frequently perform the space division and clustering when the positions of microphone arrays are changed, which will induce additional computational complexity. In this paper, we proposed a coarse-to-fine region contraction SSC (CFRC-SSC) method to reduce the computational complexity of SSC for the sound source localization algorithm. The coarse level SSC with limited computational complexity will contract the whole searching space to several candidate spaces with limited size, which will reduce the searching volume for fine level SSC without omitting the actual sound source localization. Simulation results demonstrate that the proposed CFRC-SSC show a lower computational complexity in terms of SRP function evaluation times and space clustering calculation times compared to SSC.
AB - The steered response power-phase transform algorithm (SRP-PHAT) has been widely utilized for robust sound source localization for indoor environment. Searching space clustering algorithm (SSC) is the improved version of SRP-PHAT, in which the computational complexity could be greatly reduced via the space division and clustering. However, SSC has to frequently perform the space division and clustering when the positions of microphone arrays are changed, which will induce additional computational complexity. In this paper, we proposed a coarse-to-fine region contraction SSC (CFRC-SSC) method to reduce the computational complexity of SSC for the sound source localization algorithm. The coarse level SSC with limited computational complexity will contract the whole searching space to several candidate spaces with limited size, which will reduce the searching volume for fine level SSC without omitting the actual sound source localization. Simulation results demonstrate that the proposed CFRC-SSC show a lower computational complexity in terms of SRP function evaluation times and space clustering calculation times compared to SSC.
KW - Coarse-to-fine region contraction SSC
KW - Search space clustering
KW - Sound source location
KW - Steered response power with the phase transform
KW - Time-difference of arrival
UR - http://www.scopus.com/inward/record.url?scp=84876484752&partnerID=8YFLogxK
U2 - 10.1109/ICoSP.2012.6491604
DO - 10.1109/ICoSP.2012.6491604
M3 - Conference contribution
AN - SCOPUS:84876484752
SN - 9781467321945
T3 - International Conference on Signal Processing Proceedings, ICSP
SP - 79
EP - 83
BT - ICSP 2012 - 2012 11th International Conference on Signal Processing, Proceedings
T2 - 2012 11th International Conference on Signal Processing, ICSP 2012
Y2 - 21 October 2012 through 25 October 2012
ER -