Normalisation sound norm

[JRMeyer]

>>> nmstoker
[October 30, 2019, 2:42pm]

I see in the recent PR you've
added several new features from dev, including 'sound_norm' in the
AudioProcessor.

From what I can see this normalises the output audio when it's loaded,
but it isn't (yet) set in config. This simply normalises the volume
level right, whereas the spectrogram normalisation ensures the
spectrogram is a consistent size, right?

Is sound_norm ready for people to have a go experimenting with different
values for it? Happy to give it a shot but my GPU resources are limited
so thought I'd ask first

[This is an archived TTS discussion thread from discourse.mozilla.org/t/normalisation-sound-norm]

[JRMeyer]

>>> alchemi5t
[October 31, 2019, 4:09am]

> output audio

Do you mean input? I've been trying to normalize input audio volume to
have a better training phase. Also, is normalising the spectrogram
better than normalising the audio? I didn't quite get that bit you
stated about that.

[Archived Post]

[JRMeyer]

>>> nmstoker
[October 31, 2019, 10:37am]

Sorry, yes the input audio.

[Archived Post]

[JRMeyer]

>>> nmstoker
[October 31, 2019, 1:38pm]

I'm probably not the best person to explain the spectrogram
normalisation, but it was the code for functions like this that ends
with a normalisation step (that appears to be on the spectrogram but I
could be reading that wrongly!)

github.com

#### mozilla/TTS/blob/50088cbf3ba60b139692fa1666bda9f116980cad/utils/audio.py slash #L150

<br/> return scipy.signal.lfilter([1], [1, -self.preemphasis], x)<br/> <br/> def spectrogram(self, y):<br/> <br/> if self.preemphasis != 0:<br/> <br/> D = self._stft(self.apply_preemphasis(y))<br/> <br/> else:<br/> <br/> D = self._stft(y)<br/> <br/> S = self._amp_to_db(np.abs(D)) - self.ref_level_db<br/> <br/> return self._normalize(S)<br/> <br/> def melspectrogram(self, y):<br/> <br/> if self.preemphasis != 0:<br/> <br/> D = self._stft(self.apply_preemphasis(y))<br/> <br/> else:<br/> <br/> D = self._stft(y)<br/> <br/> S = self._amp_to_db(self._linear_to_mel(np.abs(D))) - self.ref_level_db<br/> <br/> return self._normalize(S)<br/> <br/> def inv_spectrogram(self, spectrogram):<br/> <br/> '''Converts spectrogram to waveform using librosa'''<br/> <br/> S = self._denormalize(spectrogram)<br/>

[Archived Post]

[JRMeyer]

>>> alchemi5t
[October 31, 2019, 2:00pm]

Ah interesting! I'll invest some time on it tomorrow. Also interested in
knowing if the volume normalization is ready to be used.

[Archived Post]

[JRMeyer]

>>> erogol
[October 31, 2019, 3:35pm]

Yes sound norm is ready to use, I just forgot to put it to config.json.
Adn all your assumptions are correct.

'sound_norm' is useful especially for multi-speaker training.

PS. we need to implement a better config scheme. 'config.json' is
getting cumbersome to use.

[Archived Post]