  The ICASSP 2022 Acoustic Echo Cancellation Challenge is intended to stimulate
research in acoustic echo cancellation (AEC), which is an important area of
speech enhancement and still a top issue in audio communication. This is the
third AEC challenge and it is enhanced by including mobile scenarios, adding
speech recognition rate in the challenge goal metrics, and making the default
sample rate 48 kHz. In this challenge, we open source two large datasets to
train AEC models under both single talk and double talk scenarios. These
datasets consist of recordings from more than 10,000 real audio devices and
human speakers in real environments, as well as a synthetic dataset. We also
open source an online subjective test framework and provide an online objective
metric service for researchers to quickly test their results. The winners of
this challenge are selected based on the average Mean Opinion Score achieved
across all different single talk and double talk scenarios, and the speech
recognition word acceptance rate.

Audio and Speech Processing;Sound