Mostly conjecture on my part, and an anecdote: for some things, I have very specific and niche tastes that come in the form of things that are difficult to label.
Example: rap music and hiphop. For the most part, I don't enjoy it that much. There are a few things though that will make a track palatable to me (or instantly turn me off despite anything else positive about it):
- Sentimentality or romance in the lyrics
- Backing track or samples that are harmonically interesting
- No egregious sexism, misogyny, glorifying of violence, thug/gangbanger culture, etc
- Beats featuring stereotypical trap hi hats kind of annoy me
I've enjoyed tracks like Deja Vu by Post Malone, or Lucid Dreams by Juice WRLD. Browsing the rest of their discography consistently disappoints me though, because tracks like these are few and far between.
The way I assume recommendation systems are traditionally designed does not account for this. It sees me listen to these tracks, and thinks I'll probably like something by similar artists or the same artists. As far as I'm aware, Spotify's recommendation system is not aware of things like tempo, meter, tonality, themes of the lyrics, harmony, etc. and so there's no way it can pick tracks like this out from the crowd.
And why would they bother? Those are all much more technically difficult things to implement than forming correlations between IDs in a database.
That was supposed to be the value proposition of Pandora and the music genome project. I don’t think the Pandora algorithm is very good, I’d guess they’re using something simpler.
Example: rap music and hiphop. For the most part, I don't enjoy it that much. There are a few things though that will make a track palatable to me (or instantly turn me off despite anything else positive about it):
I've enjoyed tracks like Deja Vu by Post Malone, or Lucid Dreams by Juice WRLD. Browsing the rest of their discography consistently disappoints me though, because tracks like these are few and far between.The way I assume recommendation systems are traditionally designed does not account for this. It sees me listen to these tracks, and thinks I'll probably like something by similar artists or the same artists. As far as I'm aware, Spotify's recommendation system is not aware of things like tempo, meter, tonality, themes of the lyrics, harmony, etc. and so there's no way it can pick tracks like this out from the crowd.
And why would they bother? Those are all much more technically difficult things to implement than forming correlations between IDs in a database.