Acoustic room modeling has several applications. Recent results us-

ing large microphone arrays show good performance, and are helpful

in many applications. For example, when designing a better acous-

tic treatment for a concert hall, these large arrays can be used to

help map the acoustic environment and aid in the design. However,

in real-time applications – including de-reverberation, sound source

localization, speech enhancement and 3D audio – it is desirable to

model the room with existing small arrays and existing loudspeakers.

In this paper we propose a novel room modeling algorithm, which

uses a constrained room model and ℓ1-regularized least-squares to

achieve good estimation of room geometry. We present experimen-

tal results on both real and synthetic data.

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