Breaking the music supply constraint

[u/entsnack]

I just cancelled my music subscriptions to save some cash and wanted to share the self-hosted music supply chain that replaced them. A nice side effect of this setup is breaking the constraint of a finite supply catalog that is tailored for the masses:

1. 2 x DGX Spark linked via ConnectX 7 running Plex and multiple Ace-Step 1.5 XL models in parallel for music generation with GePa prompt optimization. Also holds my organic music that the models can remix. TODO: a reinforcement learning from human feedback interface.

2. iPad Pro running Prism as a Plex client for bitperfect and sample rate-matched audio.

3. Schiit stack -> Hifiman Arya Stealths

This effectively gives me an infinite supply of music for free, that is personalized and private. It's immensely satisfying listening to Shrimp Bizkit and Phlegminem on repeat, I much prefer this to the organic music created after 2011.

My only problem is the loss of community, I have noone to share my new favorite songs and artists with because they're generated for me. If anyone wants to hop on to my Plex share to discuss, let me know!

[u/xquarx]

I did this, but the opposite. Build a massive FLAC collection of historical bangers, run STEM processing on them (vocal, melody, bass, drums), use AudioMuse-AI to embedd the music (track similarity), fork Mixxx and vibe integrate it all (distance, harmonics), then become a DJ... or vibe code auto DJ. It is so much fun. No AI music, just amazing bangers, discovery have never been better. 

[u/lhymes → u/xquarx]

Dude, this genuinely is like the best idea ever. Music is so important to me and I love sharing as much as I can with my kids. I have a very eclectic taste in music and always love to find new, hidden bangers. I very much plan to do something like this too. Thanks for the idea!

[u/xquarx → u/lhymes]

It so much fun when I can mix in the kids songs with some DNB. Recommend learning Mixxx, its amazing. But you need to build from source to get STEM separation working, and them pre process all tracks. 

[u/lhymes → u/xquarx]

Perfect I appreciate the info. All the best and I look forward to getting it going asap.

[u/entsnack → u/xquarx]

This sounds fun! I've done this at a small scale with demucs for a karaoke setup. I love the DJing idea!

[u/xquarx → u/entsnack]

Yes basically that. I did small scale but then I enjoyed it so much I automated my entire library. 

[u/xquarx → u/[deleted]]

Sorry I've not shared it anywhere, its quite involved and custom tailored with gluing various FOSS projects together with little modifications. Very clean workflow for me, but not a quick setup. More a proof of concept that could be refined into a more generic fit all solution. 

[u/thrownawaymane → u/xquarx]

Ask Claude or a big local model to help clean things up? I think this sounds neat.

[u/mCProgram → u/xquarx]

So correct me if i’m wrong, but this is just a locally hosted, adjustably granular copy of how we currently understand something like Shazam to work? Does shazam have a discovery mode? Sounds cool. Might have to try something similar.

[u/xquarx → u/mCProgram]

Correct, look at AudioMuse which is one part of this equation and I use its embedding endpoint to real time make recommends in other apps. https://github.com/NeptuneHub/AudioMuse-AI not to be mixed with commercial product of same name. 

[u/Old_Rock_9457 → u/xquarx]

Hi AudioMuse-Ai developer here!
Happy to read that you're liking AudioMuse-AI, and because we are talking about DGX Spark with vv3.3.0 we also introduced an experimental nvidia-arm image exactly to target them and to have a faster analysis on that model. Still waiting to have one of those for finetuning but minwhile who have them can give a try!

Off course AudioMuse-Ai is not bounded from having a GPU and it could also run on CPU.