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Close to this question but different : Wav To Spectrogram, Back To Wav

I already posted this on StackOverflow(https://stackoverflow.com/questions/54743968/how-to-go-from-wav-file-to-spectrogram-back-to-wav-file-in-python), but I figured this question might be more suited to be here :

Here's my problem. I have some wav files. I want to create their spectrogram. Then I want to do some stuff with the spectrogram and then I want to recreate a wav file associated to the new spectrogram. I am aware that the spectrogram doesn't have the phase information, however, since I have an original file, I can (theoretically) extract the phase from the original wav file.

I want to do that in Python (if possible), do you know a good library that would allow me to do that?

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  • $\begingroup$ I'm not sure what you want to do here? How would the original phase information still mean anything sensible after you modified magnitudes? $\endgroup$
    – Marcus Müller
    Feb 19, 2019 at 14:09
  • $\begingroup$ The idea is that the modified spectrogram would represent a a "close" version of the original sound. As a result, using the original phase to recompute the sound seems a better approximation that just forgetting the phase of the original file. $\endgroup$
    – Statistic Dean
    Feb 19, 2019 at 14:23
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    $\begingroup$ Why do you want to modify the spectrogram? How is that different from regular filtering? Maybe what you want is a time-variant filter? $\endgroup$
    – MBaz
    Feb 19, 2019 at 14:31
  • $\begingroup$ Spectrogram is an image, and as such a lot of deep learning techniques are very effective on spectrograms. I want to perform spectrogram reconstruction using deep learning. The end goal is still to go back to actual sound, so I need to understand how to go from an 'updated' spectrogram and an original wav file to a new wav file. The first thing I want to test there is to use the phase from the original file, but every idea is welcomed :) $\endgroup$
    – Statistic Dean
    Feb 19, 2019 at 14:39
  • $\begingroup$ yeah, but modification of a time amplitude signal inherently has phase effects, so you can't "de-intertwine" things that easily. $\endgroup$
    – Marcus Müller
    Feb 19, 2019 at 17:01

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You need to keep the phase information, which isn't included in a spectrogram. "Spectrogram" is just the magnitude of the STFT output.

So this is conceptually the same as STFT ↔ ISTFT, which is supported in Python now:

The Examples section in the ISTFT link does exactly what you want, modifying a STFT and inverse transforming to reduce noise.

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    $\begingroup$ Thank you, I'll check that this week, and i'll come back to validate your answer if it works for me :) $\endgroup$
    – Statistic Dean
    Feb 19, 2019 at 16:13
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    $\begingroup$ Sorry for taking so much time to come back, I finally tried your suggestion, and it was what I needed. Thank you very much. $\endgroup$
    – Statistic Dean
    Mar 7, 2019 at 14:08

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