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README.md
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@ -10,7 +10,7 @@
mayavoz is a Pytorch-based opensource toolkit for speech enhancement. It is designed to save time for audio researchers. Is provides easy to use pretrained audio enhancement models and facilitates highly customisable model training.
| **[Quick Start](#quick-start-fire)** | **[Installation](#installation)** | **[Tutorials](https://github.com/shahules786/enhancer/tree/main/notebooks)** | **[Available Recipes](#recipes)** | **[Demo]()**
| **[Quick Start](#quick-start-fire)** | **[Installation](#installation)** | **[Tutorials](https://github.com/shahules786/enhancer/tree/main/notebooks)** | **[Available Recipes](#recipes)** | **[Demo](#demo)**
## Key features :key:
* Various pretrained models nicely integrated with huggingface :hugs: that users can select and use without any hastle.
@ -18,12 +18,21 @@ mayavoz is a Pytorch-based opensource toolkit for speech enhancement. It is desi
* :magic_wand: A command line tool that facilitates training of highly customisable speech enhacement models from the terminal itself!
* :zap: Supports multi-gpu training integrated with Pytorch Lightning.
## Demo
Noisy audio followed by enhanced audio.
https://user-images.githubusercontent.com/25312635/203756185-737557f4-6e21-4146-aa2c-95da69d0de4c.mp4
## Quick Start :fire:
``` python
from mayavoz.models import Mayamodel
model = Mayamodel.from_pretrained("shahules786/mayavoz-waveunet-valentini-28spk")
model("noisy_audio.wav")
model.enhance("noisy_audio.wav")
```
## Recipes

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tests/test_inference.py
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@ -27,3 +27,12 @@ def test_aggregate():
data=rand, window_size=100, total_frames=1000, step_size=100
)
assert agg_rand.shape[-1] == 1000
def test_pretrained():
from mayavoz.models import Mayamodel
model = Mayamodel.from_pretrained(
"shahules786/mayavoz-waveunet-valentini-28spk"
)
_ = model.enhance("tests/data/vctk/clean_testset_wav/p257_166.wav")