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I have the same question @auspicious3000
Here you use the one-hot encoded embedding with a lent of 82 (the number of speakers it was pretrained), but could you generate a zeros-shot general embedding like in AutoVC. If I am correct the size of the used embedding was larger in that, I assume you cannot use that here.
So to wrap up: this method with the pretrained weights works only on the 82 speakers it was trained and conditioned on if we consider only the timbre conversion?
Hi,
Did you guys experiment using a pretrained encoder for getting the speaker embedding similar to your previous work (AutoVC).
PS: Amazing work by the way!
Thanks,
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