Hi,
Thanks for sharing this project. I trained a model with my data, which is quite noisy (between -15dB - 10dB 60 hours).Noise reduced well enough, but also speech volume is quite low. I changed the parameters, and then I got pretty much the same results.
(n_window = 512 , stride = 16, selection = 5104 ). Do you recommend any changes that affect the results? Also, I'm just wondering, in Adam optimization many people use beta1 value as 0.9, is there any reason you set it to 0? Last thing I want to ask how do you calculate selection for different n_window sizes? I calculated like this:
selection = n_window * x - stride
x : could be any number.
Is this correct?
Thank you, have a nice day.
Hi, Thanks for sharing this project. I trained a model with my data, which is quite noisy (between -15dB - 10dB 60 hours).Noise reduced well enough, but also speech volume is quite low. I changed the parameters, and then I got pretty much the same results. (n_window = 512 , stride = 16, selection = 5104 ). Do you recommend any changes that affect the results? Also, I'm just wondering, in Adam optimization many people use beta1 value as 0.9, is there any reason you set it to 0? Last thing I want to ask how do you calculate selection for different n_window sizes? I calculated like this: selection = n_window * x - stride x : could be any number. Is this correct? Thank you, have a nice day.