Parametric modeling is used in all those acoustic signal enhancement applications that require to model and identify a room impulse response (RIR) in a compact yet accurate way. Fixed-pole models based on orthonormal basis functions (OBFs) provide advantages over all-zero and pole-zero models. The parameters of an OBF model can be estimated from a measured target RIR by a scalable matching pursuit algorithm called OBF-MP. However, a measurement for the RIR is usually not available, and the model parameters should be estimated from input-output data. This paper introduces a block-based version of OBF-MP for the modeling and identification of room acoustic systems, which represents an intermediate step towards a sample-based recursive implementation of the algorithm. Simulation results show modeling capabilities comparable with the original OBF-MP.

Authors: Vairetti, Giacomo; De Sena, Enzo; Catrysse, Michael; Jensen, Søren H.; Moonen, Marc; van Waterschoot, Toon
Affiliations: Aalborg University, Aalborg, Denmark; KU Leuven, Leuven, Belgium; Televic N.V., Izegem, Belgium; KU Leuven, Geel, Belgium(See document for exact affiliation information.)
AES Conference: 60th International Conference: DREAMS (Dereverberation and Reverberation of Audio, Music, and Speech) (January 2016)
Paper Number: 7-3
Publication Date: January 27, 2016
Subject: Paper Session 7

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