Pytorch based speech enhancement toolkit.
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README.md

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mayavoz is a Pytorch-based opensource toolkit for speech enhancement. It is designed to save time for audio practioners & researchers. It provides easy to use pretrained speech enhancement models and facilitates highly customisable model training.

| Quick Start | Installation | Tutorials | Available Recipes | Demo

Key features 🔑

  • Various pretrained models nicely integrated with huggingface hub 🤗 that users can select and use without any hastle.
  • 📦 Ability to train and validate your own custom speech enhancement models with just under 10 lines of code!
  • 🪄 A command line tool that facilitates training of highly customisable speech enhacement models from the terminal itself!
  • Supports multi-gpu training integrated with Pytorch Lightning.
  • 🛡️ data augmentations integrated using torch-augmentations

Demo

Noisy speech followed by enhanced version.

https://user-images.githubusercontent.com/25312635/203756185-737557f4-6e21-4146-aa2c-95da69d0de4c.mp4

Quick Start 🔥

from mayavoz.models import Mayamodel

model = Mayamodel.from_pretrained("shahules786/mayavoz-waveunet-valentini-28spk")
model.enhance("noisy_audio.wav")

Recipes

Model Dataset STOI PESQ URL
WaveUnet Valentini-28spk 0.836 2.78 shahules786/mayavoz-waveunet-valentini-28spk
Demucs Valentini-28spk 0.961 2.56 shahules786/mayavoz-demucs-valentini-28spk
DCCRN Valentini-28spk 0.724 2.55 shahules786/mayavoz-dccrn-valentini-28spk
Demucs MS-SNSD-20hrs 0.56 1.26 shahules786/mayavoz-demucs-ms-snsd-20

Test scores are based on respective test set associated with train dataset.

See tutorials to train your custom model

Installation

Only Python 3.8+ is officially supported (though it might work with Python 3.7)

  • With Pypi
pip install mayavoz
  • With conda
conda env create -f environment.yml
conda activate mayavoz
  • From source code
git clone url
cd mayavoz
pip install -e .

Support

For commercial enquiries and scientific consulting, please contact me.

Acknowledgements

Sincere gratitude to AMPLYFI for supporting this project.