Efficient Adaptive Stereo Echo Canceling Schemes Based on Simultaneous Use of Multiple State Data(Speech/Acoustic Signal Processing)(<Special Section>Digital Signal Processing)

概要

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In this paper, we propose two adaptive filtering schemes for Stereophonic Acoustic Echo Cancellation (SAEC), which are based on the adaptive projected subgradient method (Yamada et al., 2003). To overcome the so-called non-uniqueness problem, the schemes utilize a certain preprocessing technique which generates two different states of input signals. The first one simultaneously uses, for fast convergence, data from two states of inputs, meanwhile the other selects, for stability, data based on a simple min-max criteria. In addition to the above difference, the proposed schemes commonly enjoy (i) robustness against noise by introducing the stochastic property sets, and (ii) only linear computational complexity, since it is free from solving systems of linear equations. Numerical examples demonstrate that the proposed schemes achieve, even in noisy situations, compared with the conventional technique, (i) much faster and more stable convergence in the learning process as well as (ii) lower level misidentification of echo paths and higher level Echo Return Loss Enhancement (ERLE) around the steady state.
社団法人電子情報通信学会の論文
2004-08-01