wav2vec-toolkit

A collection of scripts to preprocess ASR datasets and finetune language-specific Wav2Vec2 XLSR models

This repository accompanies the 🤗 HuggingFace Community Paper on finetuning Wav2Vec2 XLSR for low-resource languages [link]

How to contribute

(Mostly identical to the huggingface/datasets contributing guide)

1. Fork the repository by clicking on the 'Fork' button on the repository's page. This creates a copy of the code under your GitHub user account.

2. Clone your fork to your local disk, and add the base repository as a remote:

   git clone [email protected]:<your Github handle>/wav2vec-toolkit.git
   cd wav2vec-toolkit
   git remote add upstream https://github.com/anton-l/wav2vec-toolkit.git

3. Create a new branch to hold your development changes:

   git checkout -b a-descriptive-name-for-my-changes

   do not work on the master branch.

4. Set up a development environment by running the following command in a virtual environment:

   pip install -e ".[dev]"

   (If wav2vec-toolkit was already installed in the virtual environment, remove it with pip uninstall wav2vec_toolkit before reinstalling it in editable mode with the -e flag.)

5. Develop the features on your branch.

6. Format your code. Run black and isort so that your newly added files look nice with the following command:

   black --line-length 119 --target-version py36 src scripts
   isort src scripts

7. Once you're happy with your implementation, add your changes and make a commit to record your changes locally:

   git add .
   git commit

   It is a good idea to sync your copy of the code with the original repository regularly. This way you can quickly account for changes:

   git fetch upstream
   git rebase upstream/main

   Push the changes to your account using:

   git push -u origin a-descriptive-name-for-my-changes

8. Once you are satisfied, go the webpage of your fork on GitHub. Click on "Pull request" to send your to the project maintainers for review.