TDOA estimation for multiple sound sources in noisy and reverberant environments using broadband independent component analysis

Journal article
(Original article)


Publication Details

Author(s): Lombard A, Zheng Y, Buchner H, Kellermann W
Journal: IEEE Transactions on Audio Speech and Language Processing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Publication year: 2011
Volume: 19
Journal issue: 6
Pages range: 1490-1503
ISSN: 1558-7916


Abstract


In this paper, we show that minimization of the statistical dependence using broadband independent component analysis (ICA) can be successfully exploited for acoustic source localization. As the ICA signal model inherently accounts for the presence of several sources and multiple sound propagation paths, the ICA criterion offers a theoretically more rigorous framework than conventional techniques based on an idealized single-path and single-source signal model. This leads to algorithms which outperform other localization methods, especially in the presence of multiple simultaneously active sound sources and under adverse conditions, notably in reverberant environments. Three methods are investigated to extract the time difference of arrival (TDOA) information contained in the filters of a two-channel broadband ICA scheme. While for the first, the blind system identification (BSI) approach, the number of sources should be restricted to the number of sensors, the other methods, the averaged directivity pattern (ADP) and composite mapped filter (CMF) approaches can be used even when the number of sources exceeds the number of sensors. To allow fast tracking of moving sources, the ICA algorithm operates in block-wise batch mode, with a proportionate weighting of the natural gradient to speed up the convergence of the algorithm. The TDOA estimation accuracy of the proposed schemes is assessed in highly noisy and reverberant environments for two, three, and four stationary noise sources with speech-weighted spectral envelopes as well as for moving real speech sources. © 2011 IEEE.



FAU Authors / FAU Editors

Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Zheng, Yuanhang
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


External institutions
Technische Universität Berlin


How to cite

APA:
Lombard, A., Zheng, Y., Buchner, H., & Kellermann, W. (2011). TDOA estimation for multiple sound sources in noisy and reverberant environments using broadband independent component analysis. IEEE Transactions on Audio Speech and Language Processing, 19(6), 1490-1503. https://dx.doi.org/10.1109/TASL.2010.2092765

MLA:
Lombard, Anthony, et al. "TDOA estimation for multiple sound sources in noisy and reverberant environments using broadband independent component analysis." IEEE Transactions on Audio Speech and Language Processing 19.6 (2011): 1490-1503.

BibTeX: 

Last updated on 2018-07-08 at 22:28