Microphone Array Position Self-Calibration from Reverberant Speech Input

Konferenz: IWAENC 2012 - International Workshop on Acoustic Signal Enhancement
04.09.2012-06.09.2012 in Aachen, Germany

Tagungsband: IWAENC 2012

Seiten: 4Sprache: EnglischTyp: PDF

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Jacob, Florian; Schmalenstroeer, Joerg; Haeb-Umbach, Reinhold (Department of Communications Engineering, University of Paderborn, Germany)

In this paper we propose an approach to retrieve the geometry of an acoustic sensor network consisting of spatially distributed microphone arrays from unconstrained speech input. The calibration relies on Direction of Arrival (DoA) measurements which do not require a clock synchronization among the sensor nodes. The calibration problem is formulated as a cost function optimization task, which minimizes the squared differences between measured and predicted observations and additionally avoids the existence of minima that correspond to mirrored versions of the actual sensor orientations. Further, outlier measurements caused by reverberation are mitigated by a Random Sample Consensus (RANSAC) approach. The experimental results show a mean positioning error of at most 25 cm even in highly reverberant environments. Index Terms — Unsupervised, geometry calibration, microphone arrays, position self-calibration