Speaker tracking on multiple-manifolds with distributed microphones

Bracha Laufer-Goldshtein; Ronen Talmon; Sharon Gannot

doi:10.1007/978-3-319-53547-0_6

Speaker tracking on multiple-manifolds with distributed microphones

Bracha Laufer-Goldshtein, Ronen Talmon, Sharon Gannot

Bar-Ilan University, Technion - Israel Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
Editors	Petr Tichavsky, Massoud Babaie-Zadeh, Olivier J.J. Michel, Nadege Thirion-Moreau
Publisher	Springer Verlag
Pages	59-67
Number of pages	9
ISBN (Print)	9783319535463
DOIs	https://doi.org/10.1007/978-3-319-53547-0_6
State	Published - 2017
Event	13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017 - Grenoble, France Duration: 21 Feb 2017 → 23 Feb 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10169 LNCS

Conference

Conference	13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017
Country/Territory	France
City	Grenoble
Period	21/02/17 → 23/02/17

Keywords

Acoustic manifold
Distributed microphones
Gaussian process
Kalman filter
Speaker tracking

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-53547-0_6

Cite this

Laufer-Goldshtein, B., Talmon, R., & Gannot, S. (2017). Speaker tracking on multiple-manifolds with distributed microphones. In P. Tichavsky, M. Babaie-Zadeh, O. J. J. Michel, & N. Thirion-Moreau (Eds.), Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings (pp. 59-67). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10169 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-53547-0_6

Laufer-Goldshtein, Bracha ; Talmon, Ronen ; Gannot, Sharon. / Speaker tracking on multiple-manifolds with distributed microphones. Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings. editor / Petr Tichavsky ; Massoud Babaie-Zadeh ; Olivier J.J. Michel ; Nadege Thirion-Moreau. Springer Verlag, 2017. pp. 59-67 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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.",

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Laufer-Goldshtein, B , Talmon, R & Gannot, S 2017, Speaker tracking on multiple-manifolds with distributed microphones. in P Tichavsky, M Babaie-Zadeh, OJJ Michel & N Thirion-Moreau (eds), Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10169 LNCS, Springer Verlag, pp. 59-67, 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017, Grenoble, France, 21/02/17. https://doi.org/10.1007/978-3-319-53547-0_6

Speaker tracking on multiple-manifolds with distributed microphones. / Laufer-Goldshtein, Bracha ; Talmon, Ronen ; Gannot, Sharon.
Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings. ed. / Petr Tichavsky; Massoud Babaie-Zadeh; Olivier J.J. Michel; Nadege Thirion-Moreau. Springer Verlag, 2017. p. 59-67 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10169 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings

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A2 - Michel, Olivier J.J.

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PB - Springer Verlag

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Y2 - 21 February 2017 through 23 February 2017

ER -

Laufer-Goldshtein B , Talmon R , Gannot S. Speaker tracking on multiple-manifolds with distributed microphones. In Tichavsky P, Babaie-Zadeh M, Michel OJJ, Thirion-Moreau N, editors, Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings. Springer Verlag. 2017. p. 59-67. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-53547-0_6

Speaker tracking on multiple-manifolds with distributed microphones

Abstract

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Conference

Keywords

All Science Journal Classification (ASJC) codes

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