What do you see missing in tts project and how do you think we can improve it

[JRMeyer]

>>> erogol
[July 17, 2019, 1:47pm]

Please here share your comments, opinions about TTS and let us discuss
together to enable a better open-sourced environment.

[This is an archived TTS discussion thread from discourse.mozilla.org/t/what-do-you-see-missing-in-tts-project-and-how-do-you-think-we-can-improve-it]

[JRMeyer]

>>> geneing
[July 18, 2019, 6:24am]

active development.
done and current status.
to checkout old git versions to use pre-trained weights. It may be
hard to do with PyTorch.
quantization.

[Archived Post]

[JRMeyer]

>>> erogol
[July 18, 2019, 12:24pm]

{.avatar

> - Better communication about the roadmap and what features are in
> active development.
> - Better information about different active branches - what's being
> done and current status.
>
}
>
> <br/> > - This is true and needed to be fixed.<br/> ><br/> }<br/> > <!-- --><br/> >
> - Backward compatibility with pre-trained models. Currently, we need
> to checkout old git versions to use pre-trained weights. It may be
> hard to do with PyTorch.
> - Better integration with WaveRNN. Maybe include it as a subproject.
> - Some work on improving deployment, e.g. weight pruning and
> quantization.

we need to be more clear.

development. We should have a more stable code-base to promise this.

fully included in TTS increases the complexity which can not be
taken with the current head count of the project. If anyone is
volunteer on this, that's always welcome.

contributions are always welcome. However, before worrying about the
deployment, I like to fill any algorithmic gap in TTS since any
change in the algorithmic level will directly effect the deployment
phase.

[Archived Post]

[JRMeyer]

>>> geneing
[July 21, 2019, 5:49pm]

It would be nice to have a place to discuss different experiments with
improving the network architecture. If we could agree on a standard
training/test set and on a standard vocoder, maybe we could compare
results of experiments done by different people. Without standard
procedure, it's no possible to tell if the improvement is due to changes
to the architecture or due to a better training set.

[Archived Post]

[JRMeyer]

>>> alchemi5t
[July 22, 2019, 6:16am]

Very inconsistent between experiments. Might want to check performance
vs the tensorflow variants. Keithito's implementation is quite
consistent between various datasets.

I am pro pytorch, but it's kinda hard to continue development here when
results are this inconsistent. I know I haven't given enough information
for you guys to work on, just wanted to make sure you guys compare
performance vs the tensorflow variants.

[Archived Post]

[JRMeyer]

>>> erogol
[July 22, 2019, 2:24pm]

We can easily discuss experiments on Github issues. If you like to run a
new one, you can just create a new issue and we go for it. I try to keep
my experiments up-to-date on Github as explained. Let me know, if it is
not enough or you have a better way.

For the vocoder, TTS's default vocoder is GL so it is always easier to
experiment using it. All the released models are also with GL vocoder,
so if anyone likes to compare results, he can just use the latest
release for the target architecture and compare with his version. I
guess, it is better to share tensorboard logs as well, if you like to
compare loss curves. Does it make sense?

All releases, except one is with LJSpeech, so all benchmarking is going
around it.

Let me know, if you have a better way to follow collaborative
experimentation.

[Archived Post]

[JRMeyer]

>>> erogol
[July 22, 2019, 2:25pm]

what you mean by inconsistent results?

[Archived Post]

[JRMeyer]

>>> alchemi5t
[July 22, 2019, 3:37pm]

That sounds pretty good! But I think it'll be better if we discuss
experiments on discourse and leave bug fixes for github issues. GL
vocoder is perfectly fine, that's what is used on the tensorflow
implementations as well.

[Archived Post]

[JRMeyer]

>>> erogol
[July 22, 2019, 3:41pm]

I just don't like to force people to have discourse account. We can tag
the issues as 'experiment', then we can easily filter them.

[Archived Post]

[JRMeyer]

>>> alchemi5t
[July 22, 2019, 3:44pm]

By inconsistent I mean, when I use similar datasets to train the tts on
the tensorflow variant(I'll link the repo soon) I dont have to tune any
hyperparameters at all there(I.E., I tune it to work well on a standard
dataset and once I hit the sweet spot, I train another model on a
different dataset with a similar composition including quality(sample
rate and a few other params) and that works out wonderfully). But on the
mozilla one, I find that, once I tune the hyper parameter to the same
standard dataset and then when I try to train a model on another
dataset, it takes ages(1-2 days) to get past just producing noise and
then it starts sounding like the person's voice but the content is just
gibberish. I am not currently invested into experimenting with the TTS
system, so I won't be able to give you concrete information to go by.
I'll be back in a week or two and I'll try and explain the situation
with a lot more concrete information!

[Archived Post]

[JRMeyer]

>>> alchemi5t
[July 23, 2019, 3:19am]

{.avatar

> I just don't like to force people to have discourse account. We can
> tag the issues as 'experiment', then we can easily filter them.

Oh that's cool too. But since I have one already, might as well build a
community here! I did believe having a discourse account was a pain, but
I've realized helping build a community is actually quite rewarding!

[Archived Post]

[JRMeyer]

>>> josh_meyer
[July 25, 2019, 6:38pm]

+1 on the WaveRNN integration

[Archived Post]