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Noise covariance matrix estimation for rotating microphone arrays

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Title: Noise covariance matrix estimation for rotating microphone arrays
Authors: Moore, A
Xue, W
Naylor, P
Brookes, D
Item Type: Journal Article
Abstract: The noise covariance matrix computed between the signals from a microphone array is used in the design of spatial filters and beamformers with applications in noise suppression and dereverberation. This paper specifically addresses the problem of estimating the covariance matrix associated with a noise field when the array is rotating during desired source activity, as is common in head-mounted arrays. We propose a parametric model that leads to an analytical expression for the microphone signal covariance as a function of the array orientation and array manifold. An algorithm for estimating the model parameters during noise-only segments is proposed and the performance shown to be improved, rather than degraded, by array rotation. The stored model parameters can then be used to update the covariance matrix to account for the effects of any array rotation that occurs when the desired source is active. The proposed method is evaluated in terms of the Frobenius norm of the error in the estimated covariance matrix and of the noise reduction performance of a minimum variance distortionless response beamformer. In simulation experiments the proposed method achieves 18 dB lower error in the estimated noise covariance matrix than a conventional recursive averaging approach and results in noise reduction which is within 0.05 dB of an oracle beamformer using the ground truth noise covariance matrix.
Issue Date: 1-Mar-2019
Date of Acceptance: 13-Nov-2018
URI: http://hdl.handle.net/10044/1/66411
DOI: 10.1109/TASLP.2018.2882307
ISSN: 2329-9290
Publisher: Association for Computing Machinery (ACM)
Start Page: 519
End Page: 530
Journal / Book Title: IEEE/ACM Transactions on Audio, Speech and Language Processing
Volume: 27
Issue: 3
Copyright Statement: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/M026698/1
Keywords: Science & Technology
Engineering, Electrical & Electronic
Covariance matrix estimation
spatial filtering
spherical harmonic analysis
adaptive estimation
moving micro-phone array
Publication Status: Published
Online Publication Date: 2018-11-19
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering