Comments (6)
@jun-danieloh the error may because the GPU is used by another process i think. About the difference, tacotron2_inference demo the real inference on deployment including save it to pb file then load and do synthesis while decode_tacotron2 inference with input is the folder ids and it used in case you want inference all samples on the folders :D.
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Thanks for your quick response. Now I understand the diferences.
I have more questions. What's the output of "tacotron2_inference"? Is it mel? Then do I need to take this mel output to Griffin_lim inference code?
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@jun-danieloh yeah, you can use that mel and pass to GL inference to check the output. You can also train vocoder like melgan or multiband melgan as vocoder :D. GL is bad quality and just use to check :D
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@dathudeptrai Got it! Thanks for your clarity.
Last question. Do you know which tensorflow version is working properly with this repo, https://github.com/Rayhane-mamah/Tacotron-2? I saw your post in this repo so ask. I guess it would be 1.15? :)
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:))) at the time i use that repo, i used tf 1.10
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@dathudeptrai Thanks :)
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Related Issues (20)
- Multi Speaker Training HOT 1
- Support Arabic Language HOT 2
- Tacotron2 Pre-training have difficulties
- Training Tacotron2 model became so slow after update HOT 1
- How do I get the RTF index HOT 1
- Japanese TTS model HOT 2
- Preprocessing error with ljspeech HOT 6
- tacotron2 parameter confusing, hop size configuration for databaker dataset is 256, not 300 HOT 1
- Installation on MacOS HOT 1
- Hifi-Gan config for Baker dataset HOT 1
- tensorflow-gpu==2.7.0 HOT 15
- Dose it support mutil speaker of chinese language ? HOT 1
- Android release as TTS engine HOT 7
- Train with another dataset HOT 2
- No module named 'tensorflow_tts' HOT 2
- Inference on MB MelGAN sounds great until testing on iOS HOT 3
- TensorFlowTTS support vietnamese HOT 2
- [MB_Melgan] Why is a model trained only generator is better than trained on both?
- support chinese HOT 2
- How to config CMakeLists.txt ? HOT 1
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