Closed CyberLykan closed 2 years ago
Haw can I get the parameters of EQ and Compressor?
Haw can I get the parameters of EQ and Compressor?
Please use the other issue you made for discussion. Your comment does not fit here.
If your results are getting cut in half or doubled, try experimenting with removing or adding // 2
from both lines.
Seems like there are still a lot of issues with this approach. :/
LibriTTS dataset is only at 24 kHz so you would need to find a new dataset to re-train at 44k
I attempted to improve DeepAFx-ST. Here's what I did.
Download the zip from https://github.com/adobe-research/DeepAFx-ST and extract it.
Open Notepad++, press CTRL+SHIFT+F, find 24000, replace 44100, set the directory, replace in files.
At this point you can safely add the checkpoints and examples.
Edit scripts/process.py Replace
x_44100 = torch.tensor(resampy.resample(x.view(-1).numpy(), x_sr, 44100))
withx_44100 = torch.tensor(resampy.resample(x.reshape(-1).numpy(), x_sr, 44100))
Underx_44100 = x_44100.view(1, -1)
insertx_44100 = x_44100[0:1, : x_44100.shape[-1] // 2]
Underx_44100 = x
insertx_44100 = x_44100[0:1, : x_44100.shape[-1]]
Replacer_44100 = torch.tensor(resampy.resample(r.view(-1).numpy(), r_sr, 44100))
withr_44100 = torch.tensor(resampy.resample(r.reshape(-1).numpy(), r_sr, 44100))
Underr_44100 = r_44100.view(1, -1)
insertr_44100 = r_44100[0:1, : r_44100.shape[-1] // 2]
Underr_44100 = r
insertr_44100 = r_44100[0:1, : r_44100.shape[-1]]
Remove
x_44100 = x_44100[0:1, : 44100 * 5]
Remover_44100 = r_44100[0:1, : 44100 * 5]
Replace
filename = os.path.basename(args.input).replace(".wav", "")
withfilename = os.path.splitext(os.path.basename(args.input))[0]
Removereference = os.path.basename(args.reference).replace(".wav", "")
Replaceout_filepath = os.path.join(dirname, f"{filename}_out_ref={reference}.wav")
without_filepath = os.path.join(dirname, f"{filename}_DeepAFx-ST.wav")
Removein_filepath = os.path.join(dirname, f"{filename}_in.wav")
Removetorchaudio.save(in_filepath, x_44100.cpu().view(1, -1), 44100)
You should be good to go!
It's possible that this approach may have broken some things not related to processing.