Comments (5)
I'm considering using TTS for entertainment purposes (e.g. for Twitch, Youtube live broadcasts), so I don't need very high quality audio.
Anyway, I was able to get enough results with about 3 hours of recording data I used, but I don't know if 3 hours of data would be enough for other cases.
Sample speech synthesis for a few sentences can be found at https://sce-tts.github.io/
Also, the voice dataset, pretrained model, and source code I used are all publicly available at https://sce-tts.github.io/#/license
So if you are interested, you can try it yourself. (Although there is no guide written in English 😢 )
The pretrained model of Glow-TTS that I released was trained for about 2.5 days using single RTX 6000.
This is a screenshot of my Tensorboard.
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I am not a maintainer of this repository, but recently I have successfully trained Glow-TTS in diffirent language(Korean).
As you said, you can modify it in almost the same way as NVIDIA/tacotron2.
You can check my commit at sce-tts/glow-tts@e9c4701
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Thanks for advice. I don't see warm start option, did you train it from scratch or did a transfer learning from pretrained model? And what about your changes to mel min & max values? What's it for?
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I don't see warm start option, did you train it from scratch or did a transfer learning from pretrained model?
I am considering using TTS commercially so I did not transfer learning from a pretrained model published for research use.
Instead, I recorded my voice for about 3 hours and trained it from scratch.
And what about your changes to mel min & max values? What's it for?
I am using Multi-band MelGAN implemented by TensorSpeech/TensorFlowTTS instead of WaveGlow as Vocoder.
In the preprocessing of TensorFlowTTS, fmin and fmax were set to 80 and 7600, so I modified the same in Glow-TTS.
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I see. So only 3 hours was enough data for training good quality voice for commercial use? Can you show any samples? Also how long and on how many GPUs you have trained it?
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Related Issues (20)
- Question regarding fine tunning HOT 15
- Question about duration loss HOT 1
- Runtime Error: Multi speaker HOT 1
- GPU required or CPU-compatible? HOT 1
- Different Languages us different amount of GPU memory
- multi speaker
- Output compared to Fastspeech2
- Models for finetuning
- Could not create monotonic_align HOT 3
- Glowtts melspectrogram to fine tune hifigan HOT 2
- RuntimeError: CUDA error: invalid device function
- ImportError: /glow-tts/monotonic_align/monotonic_align/core.cpython-38-x86_64-linux-gnu.so: failed to map segment from shared object HOT 1
- Error using mel generated from glow-tts for hifi-gan training HOT 1
- Can I apply MAS method to other model ? HOT 1
- Query : How is the Model training different from the Model training of wave glow
- Multi speaker training error HOT 11
- With out Training DDI
- An explanation for the source code of finding the alignment path in GlowTTS? HOT 2
- DDI training compared to not DDI training HOT 1
- [Question] How many iterations for the available pretrained model?
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