Description from github:
A C++ based, lightweight music and noise remover for YouTube and other internet media, using DeepFilterNet for audio enhancement.
Source post: https://www.reddit.com/r/selfhosted/comments/1h7k7fa/
I am introducing you Fast Music Remover (https://github.com/omeryusufyagci/fast-music-remover); a free and open source tool that filters internet media.
We consume, willingly or not, large amounts of media everyday, and that includes content that is emposed on us. I want to give you the choice to opt-out of them without missing out on the core content.
We’re building a feature rich media processor that is efficient, modular and cross platform. It’s being built for you! This means: clean and light APIs for programmers, containerized on GHCR for remote users, with a Web UI for anyone interested!
Today, we support background music filtering and noise removal to enhance audio quality. In the near future, we are looking at supporting multiple ML models as well as DSP modules to empower you with the tools you need to take control over the media you consume.
There is a demo video on the readme as well as clear instructions on how to use FMR. You can immediately start by getting the docker image available at: https://github.com/omeryusufyagci/fast-music-remover/pkgs/container/fast-music-remover
If you have any feedback at all, please let me know. Thank you!
I haven’t seen anyone mention that this could be a massive improvement for persons using adaptive technologies to interact with audio media. Ive personally witnessed complaints from users of hearing aids and transcription tools who get annoyed by music messing up the content they’re trying to get from a video or podcast
I don’t use a hearing aid (…yet), but I do find videos difficult when the audio mix has the ‘background’ music too loud relative to the voice.