[AUDITORY] ICASSP 2021 Acoustic Echo Cancellation Challenge [Extended deadline]

[Ross Cutler <000001144701df79-dmarc-request@xxxxxxxxxxxxxxx>]

Our team at Microsoft recently organized the Deep Noise Suppression Challenge at INTERSPEECH 2020 to help stimulate research in this important area of research. The response from that challenge exceeded our expectations with 19 teams submitting 28 models for noise suppression. The dataset and test framework continue to be cloned and forked at a good rate since the challenge, indicating it has good utility for the research community.

Another important area for speech enhancement is acoustic echo cancellation, which is still a top issue in audio communication and conferencing systems. We are submitting a proposal to organize an Acoustic Echo Cancellation Challenge at ICASSP 2021 to stimulate research in this area. The challenge will have an open source dataset for acoustic echo cancellation and detection, captured using a large-scale crowdsourcing effort. We will provide a dataset of 10,000 different real environments, audio devices, and human speakers in the following scenarios:

1. Far-end single talk, no echo path change
2. Far-end single talk, echo path change
3. Near-end single talk, no echo path change
4. Double talk, no echo path change
5. Double talk, echo path change
6. Sweep signal for RT60 estimation

Each scenario includes the loudspeaker, microphone, and loopback signal. Besides the real data, we will also provide a synthetic dataset which is useful for training, and a real anechoic chamber dataset of 1000 devices.

The challenge is for real-time acoustic echo cancellation (AEC):

• The AEC must run in less than T/2 (in ms) to process a frame of size T (in ms) on an Intel Core i5 quad-core machine clocked at 2.4 GHz or equivalent processors. Frame length T must be less than or equal to 40ms (0<T<=40ms).
• The AEC method may have a maximum of 40ms look ahead, i.e., the algorithmic delay is 40ms. To infer the current frame T (in ms), the algorithm can access any number of past frames but only 40ms of future frames (T+40ms).
• We will provide a base model implementation.
• We will provide an objective and subjective evaluation framework.
• The AEC can be a deep model, a traditional signal processing algorithm, or a mix of the two. There are no restrictions on the AEC aside from the run time and receptive field described above.
• Prizes will be awarded to the top three participants.

For the proposal, ICASSP requires us to provide them the list of potential participants with their potential title and author(s) details. If you are interested to participate in this challenge, please send ross.cutler@xxxxxxxxxxxxx the following details by August 17th.

1. A potential title of your paper. This can be updated later.
2. A potential list of authors. This can be updated later.
3. A webpage/URL of your personal webpage, LinkedIn page, or your research lab page.

We look forward to hearing back from you and we hope to see you participate in the challenge.

Regards,

Acoustic Echo Cancellation Challenge Organizers