train.sh provides minimalist arguments needed to run the code, after downloading and converting audio formats. You could eliminate the data loader stuff and feed the model with a NxCxHxT shaped tensor, where: N=batch size (256), C=channels (1), H=num filter banks (40 lmfb/mfsc) and T=time steps (200).
I also see that other repos (like clovai baseline for SR, or deepspeech.pyotrch for ASR) avoid using schedulers. I’m not sure if they have the same experience or not?!