We are surrounded by a multitude of connected devices with microphones, the signal of which should be combined for best sound quality. Thus, we recently proposed a distributed speech and audio codec that decorrelates quantization noise applying randomization. In this paper this method is extended attenuating quantization noise using Wiener filtering at the decoder. We demonstrate that this approach can be used to jointly attenuate quantization noise and background noise present at the microphones. By using orthogonal randomization matrices, computational complexity can be minimized by separating the Wiener ?lter from the inverse randomization. Our evaluation shows that Wiener filtering in combination with a randomized distributed codec is an efficient method to attenuate background and quantization noise at the decoder.
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.
The Engineering Briefs at this Convention were selected on the basis of a submitted synopsis, ensuring that they are of interest to AES members, and are not overly commercial. These briefs have been reproduced from the authors' advance manuscripts, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for their contents. Paper copies are not available, but any member can freely access these briefs. Members are encouraged to provide comments that enhance their usefulness.