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COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD

Abstract: 

In noisy and reverberant environments speech enhancement techniques such as the multi-channel Wiener filter (MWF) can be used to improve speech quality and intelligibility. Assuming that reverberation and ambient noise can be modeled as diffuse sound fields, such techniques require an estimate of the diffuse power spectral density (PSD). Recently a multi-channel diffuse PSD estimator based on the eigenvalue decomposition (EVD) of the prewhitened signal PSD matrix was proposed. The EVD-based PSD estimator is advantageous in comparison to other state-of-the-art PSD estimators, since it does not require knowledge of the relative early transfer functions of the target signal. However, computing the EVD can be computationally expensive, particularly when the number of microphones is large. In this paper we propose to reduce the complexity of the EVD-based PSD estimator by using the iterative power method to compute the eigenvalues. Since the EVD-based PSD estimator only requires the largest eigenvalues, the full EVD is not required and the power method is a well suited computationally efficient technique to estimate these eigenvalues. Experimental results show that using the PSD estimated via the power method in an MWF yields a very similar performance as using the PSD estimated via the full EVD.

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Paper Details

Authors:
Marvin Tammen, Ina Kodrasi, Simon Doclo
Submitted On:
12 April 2018 - 11:31am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Marvin Tammen
Paper Code:
AASP-P5.10
Document Year:
2018
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Document Files

ICASSP2018_Tammenetal.pdf

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[1] Marvin Tammen, Ina Kodrasi, Simon Doclo, "COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2402. Accessed: Oct. 24, 2020.
@article{2402-18,
url = {http://sigport.org/2402},
author = {Marvin Tammen; Ina Kodrasi; Simon Doclo },
publisher = {IEEE SigPort},
title = {COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD},
year = {2018} }
TY - EJOUR
T1 - COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD
AU - Marvin Tammen; Ina Kodrasi; Simon Doclo
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2402
ER -
Marvin Tammen, Ina Kodrasi, Simon Doclo. (2018). COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD. IEEE SigPort. http://sigport.org/2402
Marvin Tammen, Ina Kodrasi, Simon Doclo, 2018. COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD. Available at: http://sigport.org/2402.
Marvin Tammen, Ina Kodrasi, Simon Doclo. (2018). "COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD." Web.
1. Marvin Tammen, Ina Kodrasi, Simon Doclo. COMPLEXITY REDUCTION OF EIGENVALUE DECOMPOSITION-BASED DIFFUSE POWER SPECTRAL DENSITY ESTIMATORS USING THE POWER METHOD [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2402