Spectral feature-based nonlinear residual echo suppression

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Schwarz A, Hofmann C, Kellermann W
Publication year: 2013
Pages range: 1-4
ISBN: 978-1-4799-0972-8
ISSN: 1947-1629
Language: English


Abstract


We propose a method for nonlinear residual echo suppression that consists of extracting spectral features from the far-end signal, and using an artificial neural network to model the residual echo magnitude spectrum from these features. We compare the modeling accuracy achieved by realizations with different features and network topologies, evaluating the mean squared error of the estimated residual echo magnitude spectrum. We also present a low complexity real-time implementation combining an offline-trained network with online adaptation, and investigate its performance in terms of echo suppression and speech distortion for real mobile phone recordings. © 2013 IEEE.


FAU Authors / FAU Editors

Hofmann, Christian
Professur für Nachrichtentechnik
Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Schwarz, Andreas
Professur für Nachrichtentechnik


How to cite

APA:
Schwarz, A., Hofmann, C., & Kellermann, W. (2013). Spectral feature-based nonlinear residual echo suppression. In Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) (pp. 1-4). New Paltz, NY, US.

MLA:
Schwarz, Andreas, Christian Hofmann, and Walter Kellermann. "Spectral feature-based nonlinear residual echo suppression." Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New Paltz, NY 2013. 1-4.

BibTeX: 

Last updated on 2019-26-04 at 10:53

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