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View Code? Open in Web Editor NEWEnd-to-end waveform utterance enhancement for direct evaluation metrics optimization by fully convolutional neural networks (TASLP 2018)
End-to-end waveform utterance enhancement for direct evaluation metrics optimization by fully convolutional neural networks (TASLP 2018)
Hi everyone,
I am asking about the number of filters considered in the code and the convolution window length. Why you considered 30 number of filters and 55 as the kernel size?.
Thank you.
In the paper, it is mentioned that the model uses 300k parameters but according to my calculation, you just used 7 conv1d layers kernel size = 55 and filters = 30. Isn't total parameters = 7 * 30 * 55 + 55 (in the last layer). Which sums up to 11000 weights approx?
Am I missing something? please guide.
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