To implement a number of sound field reconstruction methods, it is often necessary to get a measure of room impulse responses (RIRs) of a region of interest. However, in many cases this requires a time-consuming effort due to repeated measuring processes. Compressed sensing can provide an alternative solution to obtain RIRs at any location in a domain. In this article we evaluate two different sparse sound field models and a compressed sensing algorithm for the creation of multiple sound zones. RIR estimates are obtained from the sparse models and used to derive the optimal loudspeaker filters. The experimental study indicates a significant improvement of the sound zone system performance from 300 to 3000 Hz using a reduced amount of RIRs.
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can
subscribe to this RSS feed.
Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.
