🤗 Hub and TensorFlowTTS integration for Inference API

Hi TensorSpeech team! I propose building on top of the existing integration with 🤗 Hub to enable the Inference API and widgets

Current Status

• With #555, users can easily download models from the Hub.

• With https://github.com/huggingface/huggingface_hub/pull/55, TensorFlowTTS is now a searchable library in the Hub.

• With the same PR, users now have access to a code snippet that shows how to load the model. You can use text-to-mel and mel-to-wav so the code snippet is different.

What can we do next? Our next step is to integrate it to the Inference API. This would make the widget in the model repos work and allow anyone to make requests to the API, which is very exciting!

The main challenge is that TTS is a two-step process: converting text to mel, and mel to speech. At the moment, every single repo only has one of the two components, so there is no way to make inference work end-to-end.

What do you think of bundling the two models? That is, in a single repo we would have Fastspeech2 and Melgan for example. We would only do this for the repos for which the Inference API is wanted, so it wouldn’t be for all of them.

Happy to hear your thoughts, Omar

cc @patrickvonplaten @julien-c

[dathudeptrai]

@osanseviero Hi, sorry for the late implementation, I just won 1st Kaggle NLP competition and now I have more free time to do this feature 😄. I want to share my solution here in case you interested in it (https://www.kaggle.com/c/coleridgeinitiative-show-us-the-data/discussion/248253), and ofc, i used HuggingFace Transformer 😄.

[dathudeptrai]

Hi @dathudeptrai.

Thanks for all the great work around TensorFlowTTS I was wondering if you got a chance to work on this.

Cheers!

😄. I’m struggling with some other stuff, I will let you know when I finish the implementation 😄. Hope it can finish this week 😄.