ICASSP 2022 Acoustic Echo Cancellation Challenge

By Ross Cutler, Ando Saabas, Tanel Pärnamaa, Marju Purin, Hannes Gamper, Sebastian Braun, Karsten Vandborg Sørensen, Robert Aichner. 2022

81 citations recorded by the source corpus.

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 word accuracy rate as a metric, and making the audio 48 kHz. 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 online objective metric service 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 rate.

Subfields: Biomedical Engineering, Computational Mechanics, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

In Computational Mechanics

In Signal Processing

Citations in the corpus

Icassp 2022 Deep Noise Suppression Challenge (2022, background): “The winning team for Track 1 [25] also won the ICASSP 2022 AEC Challenge [26], and demonstrates a single model can provide excellent AEC, DNS, and WAcc performance.”
ICASSP 2023 Deep Noise Suppression Challenge (2023, background): “Though, this was not a requirement for this challenge.”