Autoregressive moving average modeling of late reverberation in the frequency domain

Simon Leglaive, Roland Badeau, Gäel Richard

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, the late part of a room response is modeled in the frequency domain as a complex Gaussian random process. The autocovariance function (ACVF) and power spectral density (PSD) are theoretically defined from the exponential decay of the late reverberation power. Furthermore we show that the ACVF and PSD are accurately parametrized by an autoregressive moving average (ARMA) model. This leads to a new generative model of late reverberation in the frequency domain. The ARMA parameters are easily estimated from the theoretical ACVF. The statistical characterization is consistent with empirical results on simulated and real data. This model could be used to incorporate priors in audio source separation and dereverberation.

Original languageEnglish
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1478-1482
Number of pages5
ISBN (Electronic)9780992862657
DOIs
Publication statusPublished - 28 Nov 2016
Externally publishedYes
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 28 Aug 20162 Sept 2016

Publication series

NameEuropean Signal Processing Conference
Volume2016-November
ISSN (Print)2219-5491

Conference

Conference24th European Signal Processing Conference, EUSIPCO 2016
Country/TerritoryHungary
CityBudapest
Period28/08/162/09/16

Keywords

  • Autoregressive moving average model
  • Gaussian random process
  • Late reverberation
  • Statistical room acoustics

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