You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Great work! It is very impressive that DiffSpeaker can produce lower LVE and FDD while having faster inference speed. It's also surprising to me that a VAE isn't needed to construct the latents for this diffusion model beforehand.
I wonder if there will be instructions on training DiffSpeaker on other datasets apart from VOCASET and BIWI? I'm trying to train it on a dataset I collected, that is similar to VOCASET. Is it possible to provide instructions, or general guidance to point me in the right direction?
Thanks a lot in advance!
Leo
The text was updated successfully, but these errors were encountered:
Thanks for your interest in our code! This involves 1) setting up a dataset configuration within the assets directory to define the paths, as well as 2) establishing the data loader in get_data.py. Subsequently, you can 3) modify the dataset parameter in your experiment config to train using your custom dataset. We will provide the instructions in the readme file then.
Hi Eric,
Great work! It is very impressive that DiffSpeaker can produce lower LVE and FDD while having faster inference speed. It's also surprising to me that a VAE isn't needed to construct the latents for this diffusion model beforehand.
I wonder if there will be instructions on training DiffSpeaker on other datasets apart from VOCASET and BIWI? I'm trying to train it on a dataset I collected, that is similar to VOCASET. Is it possible to provide instructions, or general guidance to point me in the right direction?
Thanks a lot in advance!
Leo
The text was updated successfully, but these errors were encountered: