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3D Room Geometry Inference Using a Linear Loudspeaker Array and a Single Microphone

 
: Tuna, C.; Canclini, A.; Borra, F.; Götz, P.; Antonacci, F.; Walther, A.; Sarti, A.; Habets, E.A.P.

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IEEE ACM transactions on audio, speech, and language processing 28 (2020), S.1729-1744
ISSN: 2329-9290
ISSN: 2329-9304
Englisch
Zeitschriftenaufsatz
Fraunhofer IIS ()

Abstract
Sound reproduction systems may highly benefit from detailed knowledge of the acoustic space to enhance the spatial sound experience. This article presents a room geometry inference method based on identification of reflective boundaries using a high-resolution direction-of-arrival map produced via room impulse responses (RIRs) measured with a linear loudspeaker array and a single microphone. Exploiting the sparse nature of the early part of the RIRs, Elastic Net regularization is applied to obtain a 2D polar-coordinate map, on which the direct path and early reflections appear as distinct peaks, described by their propagation distance and direction of arrival. Assuming a separable room geometry with four side-walls perpendicular to the floor and ceiling, and imposing pre-defined geometrical constraints on the walls, the 2D-map is segmented into six regions, each corresponding to a particular wall. The salient peaks within each region are selected as candidates for the first-order wall reflections, and a set of potential room geometries is formed by considering all possible combinations of the associated peaks. The room geometry is then inferred using a cost function evaluated on the higher-order reflections computed via beam tracing. The proposed method is tested with both simulated and measured data.

: http://publica.fraunhofer.de/dokumente/N-602919.html