AI音楽
moseca
Separate vocals and instruments in the browser with Demucs.
★ 397 スターMIT
ガイドを見る →pymss-studioは、pymss-projectが公開しているオープンソースのAI音楽プロジェクトです（GitHub: pymss-project/pymss-studio）。GitHubスターは518、フォークは31で、AGPL-3.0ライセンスの下で公開されています。GitHubでの最終更新は2026年9月29日です。
A cross-platform desktop GUI for music source separation.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Compose and edit with MIDI workflows.
Faithful ports of published models.
Tweak models and pipelines freely.
Splits songs into vocals, drums, bass, and more.
Describe a track and get audio back.
Generate music without cloud APIs.
Download the source and move into the project folder.
git clone https://github.com/pymss-project/pymss-studio.git
cd pymss-studioPull in the Node packages the project needs.
npm installStart the dev server and open the printed URL.
npm run devIt is an open-source project at pymss-project/pymss-studio with 31 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
Yes for most uses, but it is AGPL-3.0 (copyleft): if you distribute modified versions, you must share your source changes too.
Typically 44.1–48kHz stereo — good enough for demos and remixes.
Separation and generation run much faster on GPU, but CPU works for short tracks.
Check the model's license — the code license and model weights may differ.
Separate vocals and instruments in the browser with Demucs.
A resource-efficient music source separation model in PyTorch.
Loss functions for training audio source separation models.
A Python inference package for music source separation models.
Friendly front-end for local AI music models, packed with quality-of-life touches.
Run splifft locally: lightweight utilities for music source separation and t.
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