free-music-demixer VS quoordinates

Hi HN,

Over the Christmas break I added multi-threading to the WASM Demucs module in freemusicdemixer

Demucs (v4 hybrid transformer) is a much higher quality model than the previous default, but it ran very slowly when limited to one worker: ~17 minutes for an average 4-minute song

I have since implemented multi-threading with WebWorkers.

If you raise the "MAX MEMORY" setting to 16 GB or 32 GB, your track will demix within 7-5 minutes, producing state-of-the-art results.

There is also support for the Demucs 6-source model which adds piano and guitar stems.

Please reach out and be loud about any bugs or UX issues you encounter!: https://github.com/sevagh/free-music-demixer/issues

* Post-processing step (bigger impact)

I tried to tackle the post-processing step in my C++ code (which would win ~1 dB in quality across all targets) but it's too tricky for now [2]. Maybe some other day.

1: https://github.com/sevagh/free-music-demixer/blob/main/examp...

2: https://github.com/sigsep/open-unmix-pytorch/blob/master/ope...

You definitely could! Funnily enough, I have a function named "justBooks()" [1] that filters the Readwise export to just book type tags, but you could use the entire export, or whatever upstream method you want. I think much like journaling, every one's use case will be catered to their own tasks/quotes/ideas, but allow me to share centralized advice. You'll definitely need: 1) a database that supports vectors, I use Postgres 2) a low friction way to get your "new" highlights from your reading practice, I use Readwise 3) an llm to "cache" transformations [2]. This transformation does an insane amount of work, and takes it to the next level in terms of utility, I wouldn't skip it.

[1] - https://github.com/bramses/quoordinates/blob/1b9d1fadaded98b...