MFNet

This is the unofficial implementation of MFNet, from paper''a Mask Free Neural Network for Monaural Speech Enhancement''

arxiv:https://arxiv.org/abs/2306.04286

I appreciate the guidance and assistance from the author. After the correction following our discussion:
1.The initial learning rate is 3e-4, correcting the value from 0.0034 in the paper.
2.The features input to the network are compressed spectra, i.e., input = sign(stdct) * sqrt(stdct).
3.DCT transformation without normalization.
I put the key code of STDCT, which may be useful for you.

Result

This experiment did not utilize the warm-up strategy mentioned in the paper. Instead, following the author's recommendation, the training parameters were set as follows:

• Initial learning rate: 3e-4
• Training for 1000 epochs
• Cosine annealing with a period of 1000 epochs
• Minimum value during cosine annealing: 1e-5

Performance of MFNet on the Voicebank+Demand (VCTK) test set:

Additionally, these are the best results on the test set obtained during the first 100 epochs of training.