Signal-Based Performance Evaluation of Dereverberation Algorithms
Author(s) -
Patrick A. Naylor,
Nikolay D. Gaubitch,
Emanuël A. P. Habets
Publication year - 2010
Publication title -
journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 25
eISSN - 2090-0155
pISSN - 2090-0147
DOI - 10.1155/2010/127513
Subject(s) - reverberation , normalization (sociology) , impulse (physics) , algorithm , computer science , impulse response , signal processing , nonlinear system , speech recognition , digital signal processing , mathematics , acoustics , physics , mathematical analysis , quantum mechanics , sociology , anthropology , computer hardware
We address the measurement of reverberation in terms of the (DRR) inthe context of the assessment of dereverberation algorithms for which we wish to quantify the level of reverberation before and after processing. The DRR is normally calculated from the impulse response of the reverberating system. However, several important dereverberation algorithms involve nonlinear and/or time-varying processing and therefore their effect cannot conveniently be represented in terms of modifications to the impulse response of the reverberating system. In such cases, we show that a good estimate of DRR can be obtained from the input/output signals alone using the Signal-to-Reverberant Ratio (SRR) only if the source signal is spectrally white and correctly normalized. We study alternative normalization schemes and conclude by showing a least squares optimal normalization procedure for estimating DRR using signal-based SRR measurement. Simulation results illustrate the accuracy of DRR estimation using SRR
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