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My own easy-to-understand implementation of the paper Jansson et al., "Singing Voice Separation with Deep U-Net Convolutional Networks"

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Deep-Learning Vocal Remover

Introduction

My own easy-to-understand implementation of the paper Jansson et al., "Singing Voice Separation with Deep U-Net Convolutional Networks" using PyTorch and librosa.

Usage

Training

  • Put audio files with instrument-only track on the left channel and mixed (with vocal) track on the right channel into the data directory.

  • Run train.py

Inference

  • Specify input media in inference.py.
  • Run inference.py
  • The result will be saved as result.wav.

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My own easy-to-understand implementation of the paper Jansson et al., "Singing Voice Separation with Deep U-Net Convolutional Networks"

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  • Python 100.0%