  The recently proposed semi-blind source separation (SBSS) method for
nonlinear acoustic echo cancellation (NAEC) outperforms adaptive NAEC in
attenuating the nonlinear acoustic echo. However, the multiplicative transfer
function (MTF) approximation makes it unsuitable for real-time applications
especially in highly reverberant environments, and the natural gradient makes
it hard to balance well between fast convergence speed and stability. In this
paper, we propose two more effective SBSS methods based on
auxiliary-function-based independent vector analysis (AuxIVA) and independent
low-rank matrix analysis (ILRMA). The convolutive transfer function (CTF)
approximation is used instead of MTF so that a long impulse response can be
modeled with a short latency. The optimization schemes used in AuxIVA and ILRMA
are carefully regularized according to the constrained demixing matrix of NAEC.
Experimental results validate significantly better echo cancellation
performance of the proposed methods.
