tsurumeso/vocal-remover
Vocal Remover using Deep Neural Networks
What it solves
It provides a way to extract instrumental tracks from songs by separating the vocals from the background music using deep learning.
How it works
The tool uses deep-learning models to process audio files and split them into two distinct tracks: one for vocals and one for instruments. It supports CPU and GPU acceleration and offers advanced options like Test-Time Augmentation (TTA) to improve separation quality and an experimental post-processing mask based on vocal volume.
Who it’s for
Musicians, audio engineers, and anyone looking to create high-quality instrumental versions of existing songs.
Highlights
- Supports both CPU and GPU inference.
- Includes Test-Time Augmentation (TTA) for better audio separation.
- Allows users to train their own custom models using their own datasets.
- Provides an experimental post-processing feature to refine the instrumental track.
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