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Implementation of Deep Complex UNet Using PyTorch
Is there pretrain model for download?
Thanks!
Hi, thanks for your code.
It seems the paper has been retracted due to data fold setting error, April 2019.
https://openreview.net/forum?id=SkeRTsAcYm
Hi,
First, thanks for sharing this code. I tried to train a model with my dataset. But it gave "Processing error!" and stop working. Could you please tell me what causes this error?
Thanks.
Hallo,
I have run this code on same dataset (DEMAND+VoiceBank). But during the training the train_metric(pesq) is much smaller than val_metric, namely, train_metirc is about 2.7 and val_metric is about 3.2. Do you have the similar situation?
May I ask the what is the package "PinkBlack"?
I see you put 'torch.tanh' directly on 'mask' produced by 'self.linear(p)' in the 'forward(self, bd)' of 'class UNet(nn.Module)' (unet.py, line 119). If I read this right, you implement 'torch.tanh' on an complex number, but it implements 'torch.tanh' on the magnitude of the complex number as published in the 'Phase-Aware Speech Enhancement with Deep Complex U-Net' paper. Are this two implementation the same? Or it should be implemented like the 'mask_processing' in https://github.com/Doyosae/Phase_aware_Deep_Complex_UNet/blob/master/model_module.py (line 73)?
Hi,
When I ran "estimate_directory.py" with a directory that contains almost 5 minutes long wav files I got a memory error. It ran with smaller wav files, but I need it to run with larger files. Could you please take a look at that? I'll try to fix it as well. Thank you for your good work.
Have a nice day
if (err_info->Nutterances < 1)
{
/printf ("Processing error!\n");/
/exit (1);/
PyErr_SetString(PyExc_RuntimeError, "processing error!");
}
Log print warnings.warn('Processing Error! return NaN........')
use older version, i see it stop at conditions err_info->Nutterances < 1 processing error! WHY?
but if i change metric="pesq" to metric="" ,training is ok!
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