Significance-aware Hammerstein group models for nonlinear acoustic echo cancellation

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Hofmann C, Hümmer C, Kellermann W
Publisher: Institute of Electrical and Electronics Engineers Inc.
Publication year: 2014
Pages range: 5934-5938
ISBN: 978-1-4799-2892-7
ISSN: 1520-6149
Language: English


Abstract


In this work, a novel approach for nonlinear acoustic echo cancellation is proposed. The main innovative idea of the proposed method is to model only the small region of the echo path around the direct path by a group of parallel Hammerstein models, to estimate a nonlinear preprocessor by correlations between the linear kernels of the Hammerstein submodels, and to describe the remaining echo path by a simple Hammerstein model with the preprocessor determined in the aforementioned way. While the computational complexity of such a system increases only slightly in comparison to a linear echo canceller, experiments with speech recordings from a smartphone in different environments confirm a significantly increased echo cancellation performance. © 2014 IEEE.


FAU Authors / FAU Editors

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


How to cite

APA:
Hofmann, C., Hümmer, C., & Kellermann, W. (2014). Significance-aware Hammerstein group models for nonlinear acoustic echo cancellation. In Proceedings of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (pp. 5934-5938). Florence, IT: Institute of Electrical and Electronics Engineers Inc..

MLA:
Hofmann, Christian, Christian Hümmer, and Walter Kellermann. "Significance-aware Hammerstein group models for nonlinear acoustic echo cancellation." Proceedings of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence Institute of Electrical and Electronics Engineers Inc., 2014. 5934-5938.

BibTeX: 

Last updated on 2019-24-04 at 13:23