Inference on pre-trained model (flowtron_ljs) speaking nonsense. about flowtron HOT 4 CLOSED

Check your text cleaners, maybe you use another arphabet or phoneme representation or you didnt include CMU dict.

Thank you for a reply.

Here's the frames I tried (200 to 500)

n200_sid0_sigma0.5.mov
n300_sid0_sigma0.5.mov
n400_sid0_sigma0.5.mov
n500_sid0_sigma0.5.mov
There's roughly 230 frames for the n400 and 290 frames for n500. And they are all still speaking alien language.

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It's normal, and It's maybe attention problem (or maybe gate problem), How many frames do you provide? Try to provide more or less frames in inference with this options python inference.py -c config.json -f models/flowtron_ljs.pt -w models/waveglow_256channels_universal_v5.pt -t "It is well know that deep generative models have a rich latent space!" -i 0 -n 400 - where 400 number of frames and its default number of frames, try to use 200 or 300. And let me know.

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Thank you for a reply.

Here's the frames I tried (200 to 500)

There's roughly 230 frames for the n400 and 290 frames for n500.
And they are all still speaking alien language.

from flowtron.

So, I tried installing a new fresh repo from this main branch without any of my commit, then fix a few lines in inference.py (remove .half(), change 'bottom' to 'lower' ), I can now generate the sound to exactly what the text input is.

Then I came back to my original repo and was suspecting that my symbols.py was the problem, since I removed all the arpabet
from them.

After adding all the arpabet back, it's now working just like the fresh one.

Thank you for your help @Bahm9919

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