PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Adaptive Combination of Volterra Kernels and its Application to Nonlinear Acoustic Echo Cancellation
Luis Azpicueta-Ruiz, Marcus Zeller, Aníbal R. Figueiras-Vidal, Jerónimo Arenas-Garcia and Walter Kellermann
IEEE Trans. Audio, Speech and Language Processing Volume 19, pp. 97-110, 2011.

Abstract

The combination of filtersconcept is a simple and flexible method to circumvent various compromises hampering the operation of adaptive linear filters. Recently, applications which require the identification of not only linear, but also non linear systems are widely studied. In this paper, we propose a combination of adaptive Volterra filters as the most versatile non linear models with memory. Moreover, we develop a novel approach that shows a similar behavior but reduces significantly the computational load by combining Volterra kernels rather than complete Volterra filters. Following an outline of the basic principles, the second part of the paper focuses on the application to non linear acoustic echo cancellation scenarios. As the ratio of the linear to non linear echo signal power is, in general, a priori unknown and time-variant, the performance of nonlinear echo cancellers may be inferior to a linear echo canceller if the non linear distortion is very low. Therefore, a modified version of the combination of kernels is developed obtaining a robust behavior regardless of the level of non linear distortion. Experiments with noise and speech signals demonstrate the desired behavior and the robustness of both the combination of Volterra filters and the combination of kernels approaches in different application scenarios.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Speech
Theory & Algorithms
ID Code:6691
Deposited By:Jerónimo Arenas-Garcia
Deposited On:08 March 2010