Comments (4)
Sorry for late response.
- Actually this project does NOT need dataset, because we use random parameters CNN.
- As for evaluation, there is not a good method like Inception Score(IS) or MSE, currently mainly based mean of score(MOS) .
This project is done a few months ago, I may elaborate it when I'm free.
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Thanks for reply. I gone through this your work. and I did. It creating random voice, and currently not able to clone any voice.
from randomcnn-voice-transfer.
@shwetagargade216 I'm not sure what do you mean by "random voice", currently it can transfer some voice texture of speaker A
to speaker B
while keeping with B
's content the result, though the transfer process is not satisfying.
Feel free to reopen this issue.
from randomcnn-voice-transfer.
@mazzzystar
@shwetagargade216
hi all
i see this project, it's nice.
itried it on 2 voicce wave to vonvert from one to othe, but how about if i want to do the conversion on a dataset ?
i have a dataset, and want to do the conversion to do it all at once, how?
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Related Issues (20)
- bad result i git!!
- Is it possible to retain a model of the voice conversion? HOT 2
- Some unclear details. HOT 1
- can't optimize a non-leaf Tensor HOT 1
- required os and python versions? HOT 3
- Input output??? HOT 1
- Question: difference between this repo and others? HOT 1
- Bad very long time to train compare the original project DmitryUlyanov
- no voice
- RuntimeError: CUDA error: unspecified launch failure HOT 1
- AttributeError: module 'librosa' has no attribute 'output' HOT 1
- Any updates to this? HOT 2
- Question
- when I run train, some problems came out: HOT 9
- Installation Environment HOT 2
- some problems HOT 17
- import torch error HOT 7
- RuntimeError: CUDA out of memory HOT 1
- Phase restoration algorithm HOT 2
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