  This paper describes aecX team's entry to the ICASSP 2023 acoustic echo
cancellation (AEC) challenge. Our system consists of an adaptive filter and a
proposed full-band Taylor-style acoustic echo cancellation neural network
(TaylorAECNet) as a post-filter. Specifically, we leverage the recent advances
in Taylor expansion based decoupling-style interpretable speech enhancement and
explore its feasibility in the AEC task. Our TaylorAECNet based approach
achieves an overall mean opinion score (MOS) of 4.241, a word accuracy (WAcc)
ratio of 0.767, and ranks 5th in the non-personalized track (track 1).
