Open Xu-Kaibo opened 1 year ago
Hey, I'm working with this model right now. There is nothing ready to be published yet, but I found some problems in this implementation. But the thing that will fix the bad pesq is to use a right stft window: Here they use a rectangle window. You can pass a better suited window like this:
clean_stft = torch.stft(input=clean_sample, n_fft=self.n_fft, window=torch.hann_window(self.n_fft, True),
hop_length=self.hop_length, normalized=True, return_complex=False)
In this case I used a "hann" window. Some other flaws:
Hope this helped and I will share my code when it's "presentable"
PESQ value of my reproduced model(3 epoch) is only 2.0438 instead of 2.818 from Mr.Filippov's experiment. I followed the steps of the provided code. But the function of calculating PESQ value can't run, so I modified it a little. The PESQ value of testset itself is 1.9306. And after denoising by the model trained after 3 epoches, the PESQ is just 2.0438. I'm so confused about where's the wrong. My PESQ calculation code is pasted below: " def metrics_score(mode, net, test_loader):
Calculate mode: "Testset"/"TestModel",
"