vocal-remover

This is a deep-learning-based tool to extract instrumental track from your songs.

Installation

Getting vocal-remover

Download the latest version from here.

Install PyTorch

See: GET STARTED

Install the other packages

cd vocal-remover
pip install -r requirements.txt

Usage

The following command separates the input into instrumental and vocal tracks. They are saved as *_Instruments.wav and *_Vocals.wav.

Run on CPU

python inference.py --input path/to/an/audio/file

Run on GPU

python inference.py --input path/to/an/audio/file --gpu 0

Train your own model

Install SoundStretch

sudo apt install soundstretch

Place your dataset

dataset/
  +- instruments/
  |    +- 01_foo_inst.wav
  |    +- 02_bar_inst.mp3
  |    +- ...
  +- mixtures/
       +- 01_foo_mix.wav
       +- 02_bar_mix.mp3
       +- ...

Offline data augmentation

python augment.py -i dataset/instruments -m dataset/mixtures -p -1
python augment.py -i dataset/instruments -m dataset/mixtures -p 1

Train a model

python train.py -i dataset/instruments -m dataset/mixtures -M 0.5 -g 0

References

• [1] Jansson et al., "Singing Voice Separation with Deep U-Net Convolutional Networks", https://ismir2017.smcnus.org/wp-content/uploads/2017/10/171_Paper.pdf
• [2] Takahashi et al., "Multi-scale Multi-band DenseNets for Audio Source Separation", https://arxiv.org/pdf/1706.09588.pdf
• [3] Liutkus et al., "The 2016 Signal Separation Evaluation Campaign", Latent Variable Analysis and Signal Separation - 12th International Conference