EURASIP Journal on Audio, Speech, and Music Processing
Volume 2007 (2007), Article ID 71495, 13 pages
doi:10.1155/2007/71495
Research Article

Detection-Guided Fast Affine Projection Channel Estimator for Speech Applications

Yan Wu Jennifer,1 John Homer,2 Geert Rombouts,3 and Marc Moonen3

1Canberra Research Laboratory, National ICT Australia and Research School of Information Science and Engineering, The Australian National University, Canberra ACT 2612, Australia
2School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane QLD 4072, Australia
3Departement Elektrotechniek, Katholieke Universiteit Leuven, ESAT/SCD, Kasteelpark Arenberg 10, Heverlee 30001, Belgium

Received 9 July 2006; Revised 16 November 2006; Accepted 18 February 2007

Academic Editor: Kutluyil Dogancay

Copyright © 2007 Yan Wu Jennifer et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In various adaptive estimation applications, such as acoustic echo cancellation within teleconferencing systems, the input signal is a highly correlated speech. This, in general, leads to extremely slow convergence of the NLMS adaptive FIR estimator. As a result, for such applications, the affine projection algorithm (APA) or the low-complexity version, the fast affine projection (FAP) algorithm, is commonly employed instead of the NLMS algorithm. In such applications, the signal propagation channel may have a relatively low-dimensional impulse response structure, that is, the number m of active or significant taps within the (discrete-time modelled) channel impulse response is much less than the overall tap length n of the channel impulse response. For such cases, we investigate the inclusion of an active-parameter detection-guided concept within the fast affine projection FIR channel estimator. Simulation results indicate that the proposed detection-guided fast affine projection channel estimator has improved convergence speed and has lead to better steady-state performance than the standard fast affine projection channel estimator, especially in the important case of highly correlated speech input signals.