Grad TTS in multispeaker setting

[ajinkyakulkarni14]

I observed that in model.py "gin_channels" is provided in DiffusionGenerator.

I would like to know if Grad-TTS supports multispeaker TTS training ?

Can you also provide pretrained model trained with LJS dataset ?

I had some difficulties on installing Horovod on GPU cluters on server side, so I changed the train.py from Horovod to torch.distributed.

Thank you for repo.

[WelkinYang]

I observed that in model.py "gin_channels" is provided in DiffusionGenerator.

I would like to know if Grad-TTS supports multispeaker TTS training ?

Can you also provide pretrained model trained with LJS dataset ?

I had some difficulties on installing Horovod on GPU cluters on server side, so I changed the train.py from Horovod to torch.distributed.

Thank you for repo.

Because the LJSpeech dataset and our internal Mandarin dataset are both single-speaker datasets, I have not tried the multi-speaker dataset. I think it is feasible to do the multi-speaker training as the glowtts do by setting the gin_channels and g.

As the pre-trained model, I would like to provide the checkpoint and I would provide it in a few months.

And I trained my model in a compute Cluster which does not support torch.distributed but horovod, so I changed the code of glowtts.