Room Impulse Response Estimation using Sparse Online Prediction and Absolute Loss
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The need to accurately and efficiently estimate room impulse responses arises in many acoustic signal processing applications. In this work, we present a general family of algorithms which contain the conventional normalized least mean squares (NLMS) algorithm as a special case. Specific members of this family yield estimates which are robust both to different noise models and choice of parameters. We demonstrate the merits of our approach to accurately estimate sparse room impulse responses in simulations with speech signals.
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Copyright 2006 IEEE. Reprinted from 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Volume 3, pages III-748 - III-751. Publisher URL: http://dx.doi.org/10.1109/ICASSP.2006.1660762 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.