TY - GEN
T1 - Speaker tracking on multiple-manifolds with distributed microphones
AU - Laufer-Goldshtein, Bracha
AU - Talmon, Ronen
AU - Gannot, Sharon
N1 - Publisher Copyright: © Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Speaker tracking in a reverberant enclosure with an ad hoc network of multiple distributed microphones is addressed in this paper. A set of prerecorded measurements in the enclosure of interest is used to construct a data-driven statistical model. The function mapping the measurement-based features to the corresponding source position represents complex unknown relations, hence it is modelled as a random Gaussian process. The process is defined by a covariance function which encapsulates the relations among the available measurements and the different views presented by the distributed microphones. This model is intertwined with a Kalman filter to capture both the smoothness of the source movement in the time-domain and the smoothness with respect to patterns identified in the set of available prerecorded measurements. Simulation results demonstrate the ability of the proposed method to localize a moving source in reverberant conditions.
AB - Speaker tracking in a reverberant enclosure with an ad hoc network of multiple distributed microphones is addressed in this paper. A set of prerecorded measurements in the enclosure of interest is used to construct a data-driven statistical model. The function mapping the measurement-based features to the corresponding source position represents complex unknown relations, hence it is modelled as a random Gaussian process. The process is defined by a covariance function which encapsulates the relations among the available measurements and the different views presented by the distributed microphones. This model is intertwined with a Kalman filter to capture both the smoothness of the source movement in the time-domain and the smoothness with respect to patterns identified in the set of available prerecorded measurements. Simulation results demonstrate the ability of the proposed method to localize a moving source in reverberant conditions.
KW - Acoustic manifold
KW - Distributed microphones
KW - Gaussian process
KW - Kalman filter
KW - Speaker tracking
UR - http://www.scopus.com/inward/record.url?scp=85013498490&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-319-53547-0_6
DO - https://doi.org/10.1007/978-3-319-53547-0_6
M3 - منشور من مؤتمر
SN - 9783319535463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 59
EP - 67
BT - Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
A2 - Tichavsky, Petr
A2 - Babaie-Zadeh, Massoud
A2 - Michel, Olivier J.J.
A2 - Thirion-Moreau, Nadege
T2 - 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017
Y2 - 21 February 2017 through 23 February 2017
ER -