1#Packet loss simulator 2 3This code is an attempt at simulating better packet loss scenarios. The most common way of simulating 4packet loss is to use a random sequence where each packet loss event is uncorrelated with previous events. 5That is a simplistic model since we know that losses often occur in bursts. This model uses real data 6to build a generative model for packet loss. 7 8We use the training data provided for the Audio Deep Packet Loss Concealment Challenge, which is available at: 9 10http://plcchallenge2022pub.blob.core.windows.net/plcchallengearchive/test_train.tar.gz 11 12To create the training data, run: 13 14`./process_data.sh /<path>/test_train/train/lossy_signals/` 15 16That will create an ascii loss\_sorted.txt file with all loss data sorted in increasing packet loss 17percentage. Then just run: 18 19`python ./train_lossgen.py` 20 21to train a model 22 23To generate a sequence, run 24 25`python3 ./test_lossgen.py <checkpoint> <percentage> output.txt --length 10000` 26 27where <checkpoint> is the .pth model file and <percentage> is the amount of loss (e.g. 0.2 for 20% loss). 28