Exploiting Echo Path Priors for Enhanced Stereo Acoustic Echo Cancellation

Adaptive filters have long served to model echo paths in stereo acoustic echo cancellation (SAEC). In modern devices such as mobile phones and smart speakers, the fixed geometry of loudspeakers and microphones allows a priori echo paths to be identified. However, this prior knowledge remains underexplored. In this paper, we propose an enhanced multichannel state-space frequency-domain adaptive filtering (MCSSFDAF) algorithm for SAEC, which is informed by a priori echo path energy. By dynamically adjusting the process noise covariance in MCSSFDAF based on tracked misalignment between estimated and prior echo paths, our method achieves faster convergence and lower misalignment. Experiments with both simulated and real-world recordings validate the algorithm’s efficacy, demonstrating accelerated reconvergence during echo path changes and superior performance across diverse scenarios.