ICASSP 2023 Acoustic Echo Cancellation Challenge

TL;DR

The ICASSP 2023 Acoustic Echo Cancellation Challenge aims to advance research in AEC by providing new datasets, tracks, and evaluation tools, fostering innovation in speech enhancement for audio communication.

Contribution

This challenge introduces a second track for personalized AEC, reduces latency to 20ms, and provides large open-source datasets and evaluation frameworks for the research community.

Findings

Multiple top-performing models achieved high MOS scores.

The challenge demonstrated effective methods for personalized echo cancellation.

Open datasets and tools facilitated rapid testing and benchmarking.

Abstract

The ICASSP 2023 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and is still a top issue in audio communication. This is the fourth AEC challenge and it is enhanced by adding a second track for personalized acoustic echo cancellation, reducing the algorithmic + buffering latency to 20ms, as well as including a full-band version of AECMOS. 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 open source an online subjective test framework and provide an objective metric for researchers to quickly test their results. The winners of this challenge were selected based on the average mean opinion score (MOS) achieved across all scenarios and the word accuracy (WAcc) rate.