Has anyone figured out a way to use this algorithm to due transfer learning?
Say I train with 100 speakers and want to train the model with an additional 20 speakers. It appears that you have to retrain from the start rather than adding a set of 20 new latent spaces and training this new data.
Anyone tried this? Would be great to be able to transfer what's been learned, but tough on GANs.
Bests,
philip
Has anyone figured out a way to use this algorithm to due transfer learning?
Say I train with 100 speakers and want to train the model with an additional 20 speakers. It appears that you have to retrain from the start rather than adding a set of 20 new latent spaces and training this new data.
Anyone tried this? Would be great to be able to transfer what's been learned, but tough on GANs.
Bests,
philip