Spatio-Temporal Audio Enhancement Based on IAA Noise Covariance Matrix Estimates

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Abstract

A method for estimating the noise covariance matrix in a mul- tichannel setup is proposed. The method is based on the iter- ative adaptive approach (IAA), which only needs short seg- ments of data to estimate the covariance matrix. Therefore, the method can be used for fast varying signals. The method is based on an assumption of the desired signal being harmonic, which is used for estimating the noise covariance matrix from the covariance matrix of the observed signal. The noise co- variance estimate is used in the linearly constrained minimum variance (LCMV) filter and compared to an amplitude and phase estimation (APES) based filter. For a fixed number of samples, the performance in terms of signal-to-noise ratio can be increased by using the IAA method, whereas if the filter size is fixed and the number of samples in the APES based filter is increased, the APES based filter performs better.
Original languageEnglish
Title of host publication2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014)
Number of pages5
PublisherIEEE
Publication date2014
Pages934 - 938
ISBN (Print)9781479946037
Publication statusPublished - 2014
Event22nd European Signal Processing Conference - Lisbon, Portugal
Duration: 1 Sept 20145 Sept 2014

Conference

Conference22nd European Signal Processing Conference
Country/TerritoryPortugal
CityLisbon
Period01/09/201405/09/2014

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