-
Notifications
You must be signed in to change notification settings - Fork 800
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Some questions #18
Comments
Hi,
We have different train/valid split. But generally, the preprocessing steps is the same and the mean/var of our training very close. So let say, i believe it's compatible, you can use Tacotron, Fastpeech generated from this repo and use pretrained models from ParallelWaveGAN. Even it's not compatible, you still can combine by de-norm my mel-spectrogram based on my stats then re-norm based-on kan-bayashi's Parallelwavegan stats :)).
To know how to inference, you can see detail at decode_tacotron2.py or decoder_melgan.py in examples directory. Melgan-STFT is melgan but training with Multi-resolution STFT loss so it's inference same as Melgan original. I will implement AutoModel Class to inference all combinations in the near future :)). Atleast, i will provide google colab soon. |
@dathudeptrai |
@ZDisket great :)). I just uploaded Tacotron pretrained 120K. I'm training multiband melgan, it will 3x faster and improve quality compared with melgan-stft :D. |
@dathudeptrai Very nice, I have a lot of hope for this repo's Multi-Band MelGAN since I can't get kan-bayashi's to work. It'll be optimal for a user-friendly Windows GUI front end. I'll also retrain my Tacotron2 on the new one. |
why mb-melgan on kan-bayashi not worked ? |
@dathudeptrai All my predictions had heavy metallic noise, and when it reaches the discriminator train start steps (on another training run) they all become pure noise. |
okay, let see how mb melgan on this repo help you. It will finish training progress on saturday, i think :D. |
@dathudeptrai |
The text was updated successfully, but these errors were encountered: