replicate audio effects by LSTM. based on coz-a/Audio-Effect-Replicator.
Train audio effects by setting dry sound as X, effected sound as Y and predict audio effect for new given sound file.
train.py -- training main program
config.yml -- define parameters and the list of sound file.
predict.py -- predict by using trained model and out .nnp file.
fx_replicator.py -- helper program for train.py and predict.py
sudo pip3 install -r requirements.txt
training
python3 train.py
You can use the tensorboard to monitor your learning status.
inferencing using training model
python3 predict.py -i ./data/testdata1-2.wav -m checkpoint\date and time\best_result.pth
you need to prepare WAV file as monoural 32bit signed int(uncompessed)format.
Using the created training model,
Inference operation can be performed not only on a PC with high processing power
but also on Jetson Nano and Raspberry pi.