Comments (1)
Good question, we actually haven't tried. We definitely believe that the model performs some "collapse" of similar audio on the same representation, and it eliminates some of the variability that might occur between two similar audios (e.g. phase difference, white noise components). Note that we have good reasons to believe the representation is mostly at the acoustic level. Thus semantic comparisons (e.g. two musics with the same genre, or two people talking of the same topic) wouldn't be close in the latent space.
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Related Issues (20)
- Changing existing models and training them HOT 1
- RuntimeError: No audio I/O backend is available HOT 5
- Codebook expiration does not take effect at all HOT 2
- MS-STFTDiscriminator: Why concatenation is done in a form of padding the real part?
- RVQ's password book
- training dataset
- Low quality of the reconstruct audio๏ผ HOT 2
- Interpolation between two audio clips? HOT 1
- License of the weights?
- Streaming example? HOT 1
- Encoding Long Audio Clips HOT 1
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