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https://github.com/storytold/storyteller-ml.git
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e4267f607b77402223356abb72597cc8f073d3f1
tts-core
The core TTS models that power FakeYou.
I'm in the progress of pulling these out of the service monorepo so we can iterate faster.
How This Works
We have a Rust monolith that controls the user interface, account system, and all the database CRUD operations. It doesn't do any ML work itself or have any attached GPUs.
There are a series of worker pods ("jobs") that pull from work queues and run inference, then upload the results.
The jobs are written in Rust and either shell out to Python code or call an in-container Python server that attempts to LRU cache models in memory.
TODO
Core cleanup
- Cleanup Tacotron code
- Integrate WaveGlow and HifiGan more cleanly
- Define the HTTP server interface
- Define the model checking interface
- Clean up in-memory LRU caching
- There are two copies of Nemo. Why? Clean this up.
- Deployability
- Clean up requirements.txt and upgrade packages
- Clean up Dockerfile
Make the models sound better
-
Arpabet
- G2P
- Arpabet custom dictionary
- User-supplied Arpabet strings in braces
-
Word break down 888 -> eight hundred eighty eight
-
Support I18N
- Accent character support
Introduce new models
- TalkNet
- GlowTTS + MelGan (vocoder)
- Make these work under the same venv
Lots more I haven't covered yet...
Description
Languages
Jupyter Notebook
66%
Python
28.1%
C++
4.5%
C
0.4%
Shell
0.4%
Other
0.3%


