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I've found most recommendation systems in general don't grasp the distinctions in genre that are in metal, or the stylistic differences. Most stuff is just tagg

I've found most recommendation systems in general don't grasp the distinctions in genre that are in metal, or the stylistic differences. Most stuff is just tagged "METAL", when there is a huge difference between grind, funeral doom, or atmo-black. Even within a genre there can be differences it doesn't really capture, like tech-death: you might call Beyond Creation and Warp Chamber both tech-death, but in reality they are pretty far from each other even though they are both technical in a tech-deathy way.

CrypticShift 4y ago
It depends on how the recommendation system defines its music genres. Spotify uses audio spectral features to automatically delineate tracks into styles. Last.fm and RateYourMusic (who added recommendations recently) rely on human taggers. So, they may give you better results genre-wise.
kixiQu 4y ago
How do you find the https://everynoise.com/ https://everynoise.com/ categories to fare at this?
- CrypticShift 4y ago
  This is Spotify’s list of "genres". To be fair (and more exact) Spotify data scientists detect patterns in the audio spectral features and use them to manually create/add new genres. The "collective wisdom" nature of last.fm and RYM will often give better results/phraseology. You could say that Spotify could also be data mining these Music Social Media sites! My own research does not show this to be true (at a large scale anyway). But they should (and pay them for it)
  - kixiQu 4y ago
    I mean, I'm pretty sure it is not just audio spectral features used, though I can't find a citation either way. (I am sure because the language distinctions make clear that we are at least making heavy use of metadata if not actual social patterns in listening, but the latter is explicitly heavily used elsewhere on the site, so...) Also, if we're being exact, it's the work of Glenn McDonald under the auspices the Echo Nest, which is now owned by Spotify, but it isn't the be-all-end-all of how Spotify models genres under the hood. What I was curious about is how /u/beezlebroxxxxxx perceived it to do at the metal genres, simply because Glenn McDonald is himself a metal genre fan (https://www.furia.com/ https://www.furia.com/), so I'd've expected that to work decently well.

CrypticShift 4y ago

It depends on how the recommendation system defines its music genres. Spotify uses audio spectral features to automatically delineate tracks into styles. Last.fm and RateYourMusic (who added recommendations recently) rely on human taggers. So, they may give you better results genre-wise.

kixiQu 4y ago

How do you find the https://everynoise.com/ https://everynoise.com/ categories to fare at this?

CrypticShift 4y ago
This is Spotify’s list of "genres". To be fair (and more exact) Spotify data scientists detect patterns in the audio spectral features and use them to manually create/add new genres. The "collective wisdom" nature of last.fm and RYM will often give better results/phraseology. You could say that Spotify could also be data mining these Music Social Media sites! My own research does not show this to be true (at a large scale anyway). But they should (and pay them for it)
- kixiQu 4y ago
  I mean, I'm pretty sure it is not just audio spectral features used, though I can't find a citation either way. (I am sure because the language distinctions make clear that we are at least making heavy use of metadata if not actual social patterns in listening, but the latter is explicitly heavily used elsewhere on the site, so...) Also, if we're being exact, it's the work of Glenn McDonald under the auspices the Echo Nest, which is now owned by Spotify, but it isn't the be-all-end-all of how Spotify models genres under the hood. What I was curious about is how /u/beezlebroxxxxxx perceived it to do at the metal genres, simply because Glenn McDonald is himself a metal genre fan (https://www.furia.com/ https://www.furia.com/), so I'd've expected that to work decently well.