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For the nonstationary algorithm, options to return sig_stft_denoised and sig_mask could be super useful for a few use cases
If noisereduce is being incorporated into an audio processing pipeline, returning sig_stft_denoised could be used for further spectral methods, rather than risking loss of info converting from spectrum to signal to spectrum again.
When trying to get the parameters right for challenging cases, getting back the sig_mask would allow for visual inspection of the effect of each parameter change.
The text was updated successfully, but these errors were encountered:
Hi Josef,
Thanks for the suggestion. Do you want to make a PR with this option
(defaulting to normal)? I’m in the woods for the summer away from a
computer but can pull it in when I get back.
On Fri, Jul 29, 2022 at 10:24 Josef Fruehwald ***@***.***> wrote:
For the nonstationary algorithm, options to return sig_stft_denoised and
sig_mask could be super useful for a few use cases
1. If noisereduce is being incorporated into an audio processing
pipeline, returning sig_stft_denoised could be used for further
spectral methods, rather than risking loss of info converting from spectrum
to signal to spectrum again.
2. When trying to get the parameters right for challenging cases,
getting back the sig_mask would allow for visual inspection of the
effect of each parameter change.
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Harvard Medical School
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For the nonstationary algorithm, options to return
sig_stft_denoised
andsig_mask
could be super useful for a few use casessig_stft_denoised
could be used for further spectral methods, rather than risking loss of info converting from spectrum to signal to spectrum again.sig_mask
would allow for visual inspection of the effect of each parameter change.The text was updated successfully, but these errors were encountered: