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Kostis-S-Z authored Jan 30, 2025
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<p align="center"><img src="./images/Blueprints-logo.png" width="35%" alt="Project logo"/></p>

This blueprint guides you to ...
This blueprint enables you to create your own [Speech-to-Text](https://en.wikipedia.org/wiki/Speech_recognition) / Automatic Speech Recognition (ASR) dataset, or use the [Common Voice](https://commonvoice.mozilla.org/) dataset, to finetune an ASR model to improve performance for your specific language & use-case. All of this can be done locally (even on your laptop!) ensuring no data leaves your machine, safeguarding your privacy.

📘 To explore this project further and discover other Blueprints, visit the [**Blueprints Hub**](https://developer-hub.mozilla.ai/blueprints/create-your-own-tailored-podcast-using-your-documents).

### 👉 📖 For more detailed guidance on using this project, please visit our [Docs here](https://mozilla-ai.github.io/Blueprint-template/)

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## Quick-start

1. Use a virtual environment and install dependencies: `pip install -e .` & install [ffmpeg](https://ffmpeg.org) e.g. for Ubuntu: `sudo apt install ffmpeg`, for Mac: `brew install ffmpeg`
2. (Optional) Create your own Speech-to-Text dataset by running `python demo/make_local_dataset_app.py`
3. Configure `config.yaml` with the model, dataset and hyperparameters of your choice.
4. Finetune Whisper by running `python src/speech_to_text_finetune/finetune_whisper.py`
5. Use the transcription app to test any HuggingFace STT model with your own voice/recordings by running `python demo/transcribe_app.py`



## Troubleshooting

> I am getting this error: `ValueError: ffmpeg was not found but is required to load audio files from filename`.
Follow the installation instructions for your OS from this link: https://ffmpeg.org/download.html, e.g. for Ubuntu: `sudo apt install ffmpeg`

## License

This project is licensed under the Apache 2.0 License. See the [LICENSE](LICENSE) file for details.
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