You can pick something out of our road map. We keep the progess of the project in this simple issue thread. It has new model proposals or developmental updates etc.
If possible, please consider sharing your pre-trained models in any language (if the licences allow for you to do so). We will include them in our model catalogue for public use and give the proper attribution, whether it be your name, company, website or any other source specified.
This model can be shared in two ways:
1. Share the model files with us and we serve them with the next 🐸 TTS release.
2. Upload your models on GDrive and share the link.
Models are served under `.models.json` file and any model is available under TTS CLI or Server end points.
Either way you choose, please make sure you send the models [here](https://github.com/coqui-ai/TTS/issues/380).
6. Explain your code using [Google Style](https://google.github.io/styleguide/pyguide.html#381-docstrings) docstrings.
7. Add your tests to our test suite under ```tests``` folder. It is important to show that your code works, edge cases are considered, and inform others about the intended use.
8. Run the tests to see how your updates work with the rest of the project. You can repeat this step multiple times as you implement your changes to make sure you are on the right direction.
```bash
$ make tests
```
9. Format your code. We use ```black``` for code and ```isort``` for ```import``` formatting.
```bash
$ make style
```
10. Run the linter and correct the issues raised. We use ```pylint``` for linting. It helps to enforce a coding standard, offers simple refactoring suggestions.
```bash
$ make lint
```
11. When things are good, add new files and commit your changes.
```bash
$ git add my_file1.py my_file2.py ...
$ git commit
```
It's a good practice to regularly sync your local copy of the project with the upstream code to keep up with the recent updates.
