Conv-TASNET:

Model with SDR = 16.7 (15.0 in the paper) on WJS0-2speaker dataset

You can find the oringnal paper TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation. The testing results are shown as follows:

Function

dataset.py: read the data into the model
Tasnet_model.py：the forword network
Tasnet_train.py：the main function to run
trainer.py：calculate the loss and for training and testing
utils.py： process the raw audio and other useful functions
train.yaml: all the parameters used in the model
test.py：separate the mixed audio and calculate SDR
loss/convTasnet_batch_12.file: the loss for each epoch during training stage
loss/test_SDR.file: the SDR on the testing set (step by 10 samples)
log/: the loss curves for tensorboard

Training stage：

from the beginning: remove the line with "trainer.rerun" in Tasnet_train.py, use "trainer.run" instead
from a trained model: remove the line with "trainer.run" in Tasnet_train.py，use "trainer.rerun" instead, and change the "model_path" in train.yaml/temp