Hi author,

When I am training your code. I printed the input tensor and it has a value matrix as in the below picture.
Here, what is the meaning of negative and positive values? Can you explain it to me?

When I am running the code, it prompts me that the size of the data and the model do not match. How can I solve this issue?

hello,
i have run your code, but the loss is hard to get 5e-7, specifically,It converges when the loss reaches 5e-6. Is there such a big difference between different data sets?

The version I am using is TensorFlow2.4.1, but the first epoch of training shows a loss of nan

Dear author, when I run your code, it appears this errors as in figure 1 below.

So, how can I fixe it? In figure 2 is folder for this code. The "path to save the trained datatrain" folder does not have any created file after running main.py file.
Many thanks.

***************** start train *****************
WARNING:tensorflow:_input is not a valid node name. Accepted names conform to Regex /re.compile('^[A-Za-z0-9.][A-Za-z0-9_.\\/>-]$')/
WARNING:tensorflow:_input is not a valid node name. Accepted names conform to Regex /re.compile('^[A-Za-z0-9.][A-Za-z0-9_.\\/>-]$')/

Dear author,

I am trying the test file following your main file.
but I don't know how to get three folders as in figure

Please give me some of suggestion, sir.
Thanks!

I downloaded noise_trainset_28spk_wav from Edinburgh DataShare as a dataset, and changed the sampling rate in the code to sr=48kHz according to the information given by the website, and generated the corresponding .tfrecords file.
When I run main.py now, I'm told UnicodeDecodeError: 'utf-8' codec can't decode byte 0xbe in position 77: invalid start byte, and can't find the cause of the problem so far.

why the channel output(8128128) is larger than the source size(128*128)? It is unfair for the tradition baseline!

I use the clean_trainset_28spk_wav.zip (2.315Gb)
take error "Sampling rate is expected to be 8kHz!"

Dear author, I would like to get your Testing Stage code file as described in your paper.
Best wishes!