Room Reverberation Reconstruction: Interpolation of the Early Part Using Compressed Sensing

This paper deals with the interpolation of the Room Impulse Responses (RIRs) within a whole volume, from as few measurements as possible, and without the knowledge of the geometry of the room. We focus on the early reflections of the RIRs, that have the key property of being sparse in the time domai...

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Bibliographic Details
Published in:IEEE transactions on audio, speech, and language processing speech, and language processing, 2013-11, Vol.21 (11), p.2301-2312
Main Authors: Mignot, Remi, Daudet, Laurent, Ollivier, Francois
Format: Article
Language:English
Subjects:
Acoustics
Algorithms
Applied sciences
Arrays
Biomechanics
Compressed
Compressed sensing
Detection
Detection, estimation, filtering, equalization, prediction
Dictionaries
Electromagnetic compatibility
Estimates
Exact sciences and technology
Image reconstruction
Information, signal and communications theory
Interpolation
Matching pursuit algorithms
Mechanics
microphone arrays
Microphones
Physics
Reconstruction
room impulse responses
Sampling, quantization
Signal and communications theory
Signal, noise
source localization
Telecommunications and information theory
Three dimensional
Vectors
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Summary:This paper deals with the interpolation of the Room Impulse Responses (RIRs) within a whole volume, from as few measurements as possible, and without the knowledge of the geometry of the room. We focus on the early reflections of the RIRs, that have the key property of being sparse in the time domain: this can be exploited in a framework of model-based Compressed Sensing. Starting from a set of RIRs randomly sampled in the spatial domain of interest by a 3D microphone array, we propose a modified Matching Pursuit algorithm to estimate the position of a small set of virtual sources. Then, the reconstruction of the RIRs at interpolated positions is performed using a projection onto a basis of monopoles, which correspond to the estimated virtual sources. An extension of the proposed algorithm allows the interpolation of the positions of both source and receiver, using the acquisition of four different source positions. This approach is validated both by numerical examples, and by experimental measurements using a 3D array with up to 120 microphones.
ISSN:1558-7916
2329-9290
1558-7924
2329-9304
DOI:10.1109/TASL.2013.2273662