Acoustic echo cancellation using Gaussian processes

Abstract

In this paper Gaussian process is applied to linear and nonlinear acoustic echo cancellation. Gaussian process is a kernel method in which predictions to new inputs are made based on the linear combination of kernel functions evaluated at each training data. First order acoustic echo-path is modeled by a linear equation of input data and second order acoustic echo-path is modeled by the second order polynomials. The performance of the cancellation is evaluated by white signal, stationary colored signal, non-stationary colored signal and real speech data. It is shown that more than 70 dB echo cancellation can be acieved within 400 ms. © 2009 Springer Berlin Heidelberg.