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Can you please give info on the data used for training the pre-trained models, both for AutoVC and speaker embedding? If you trained on a subset of a larger database, please let me know such info as well.
Best,
Pravin
The text was updated successfully, but these errors were encountered:
speaker embedding is trained by "the combination of VoxCeleb1 (Nagrani et al., 2017) and Librispeech (Panayotov et al., 2015) corpora, where there are a total of 3549 speakers"
vocoder: pre-trained the WaveNet vocoder using the method described in Shen et al. (2018) on the VCTK corpus
autoVC(content encoder&decoder): VCTK corpus, which has 109 speakers; but in paper, one task uses 20 speakers, another task uses 40speakers; And we don't know which speakers author used
We are trying to re-implement the same loss on VCTK, let's find out more wisdom on author's work togethor~
Thanks for the code.
Can you please give info on the data used for training the pre-trained models, both for AutoVC and speaker embedding? If you trained on a subset of a larger database, please let me know such info as well.
Best,
Pravin
The text was updated successfully, but these errors were encountered: