Any track becomes a game soundtrack

Loop any section forever · hit «Next» · the music evolves — seamlessly, on the beat

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In games, music reacts: stay in the tavern and its theme loops forever; descend into the dungeon and the score darkens with you. musslop does this with any mp3.

Drop a track → AI finds the musical structure → every section becomes a perfect loop → you drive the music live, like a game audio engine — no editing skills required.

Why it feels magic

Built for the game table

The flagship use case is tabletop RPG: turn any track into a location theme. The party lingers in the tavern — the tavern section loops. They open the dungeon door — one keypress, and the music descends with them, on the beat, mid-session. There is even a Tavern UI theme (wood, parchment & gold) switchable in the header.

Also great for: game dev prototyping (audition adaptive behaviour before wiring FMOD/Wwise, export loop WAVs), streaming, practice looping, focus music.

Quick start

Linux / macOS:

git clone https://github.com/Siziff/musslop.git && cd musslop
./setup.sh   # creates .venv, installs everything (incl. a bundled ffmpeg)
./run.sh     # → http://localhost:8801

Windows (needs Python 3.10+ with "Add to PATH" checked):

git clone https://github.com/Siziff/musslop.git
cd musslop
setup.bat
run.bat      # → http://localhost:8801

ffmpeg is downloaded automatically with the dependencies — no manual install needed.

Optional AI engines (each is one command, both auto-detected by run.sh):

Linux / macOS:

./setup-ai-songformer.sh  # SongFormer 2025 + Beat This! — newer, faster,
                          # best on pop/rock/electronic; plain pip, no compilers
./setup-ai-allin1.sh      # All-In-One 2023 + Demucs — steadier on orchestral,
                          # also powers the stem "layers" feature

Windows:

setup-ai-songformer.bat   # needs git in PATH; ~15 min, ~4 GB

The All-In-One engine is not supported natively on Windows (its NATTEN dependency needs a source build); use WSL2 with the Linux script if you need it. SongFormer covers structure analysis fully, and the stem "layers" feature also works through it on Windows.

Works fully offline after setup. First AI analysis of a track: ~1 min on GPU, a few minutes on CPU; results are cached — reopening is instant.

Under the hood

1. Beat & downbeat tracking — onset envelope + dynamic programming (Ellis 2007)
2. Structure — neural (All-In-One, WASPAA 2023) or Foote novelty on beat-synced chroma+MFCC+RMS self-similarity
3. Loop-aware refinement — boundaries move along downbeats maximizing loop closure quality (head/tail spectral similarity), phrase lengths (4/8 bars) and transition audibility
4. Build-up detection — normalized RMS slope + trend R² + spectral-centroid rise
5. Playback — every loop pass is an independent AudioBufferSourceNode; transitions land on loop/phrase boundaries with micro-fades, tails and bass-swap

Built on the shoulders of: SongFormer (ASLP-lab, CC-BY-4.0) · All-In-One (Kim & Nam, MIT) · Beat This! (CPJKU, MIT) · Demucs · librosa — plus classic MIR: Ellis 2007 (beat tracking), Foote 2000 (novelty segmentation).

API

Troubleshooting

1. curl http://localhost:8801/api/health → expect {"status":"ok", ...}
2. Blank page → hard-refresh (Ctrl+F5), check browser console (F12)
3. Port busy → ./run.sh frees it; manually: lsof -ti tcp:8801 | xargs kill
4. No sound → click the ♪? self-test in the volume box (bottom-right)
5. Server errors → server.log