This repository will contain data and example code for the INTERSPEECH 2022 Audio Deep Packet Loss Concealment Challenge.
You can find more information about the challenge and how to enter at https://aka.ms/plc_challenge
If you have any questions, please contact us via e-mail at plc_challenge@microsoft.com
The training and validation dataset has now been released and is available as a tar.gz archive:
https://plcchallenge2022pub.blob.core.windows.net/plcchallengearchive/test_train.tar.gz
The blind set is now also available:
https://plcchallenge2022pub.blob.core.windows.net/plcchallengearchive/blind.tar.gz
Update (24. March 2022): The reference data for the blind set is now available:
https://plcchallenge2022pub.blob.core.windows.net/plcchallengearchive/blind_set_reference.tar.gz
Please make sure to submit your results by the deadline, March 8th 2022 23:59 AoE.
Additional information about the data included can be found in our challenge paper, and information about how to register for the challenge can be found at https://aka.ms/plc_challenge .
To help with model development, we will provide access to a prototype PLC-MOS neural model API which will provide MOS score estimates for audio files with packet loss concealment applied. For further details on how to get access to this API, refer to https://aka.ms/plc_challenge . You can find an API usage example in PLC-MOS-API-Example.ipynb .
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