Back when humans still did work, the Music Genome Project had people listen to songs and try to break them down into little "genes" of metadata, everything from "vocal harmonies" to "minor chords" to "strong lyrical presence". It worked way better than the automated systems, IMO, and gave rise to Pandora: https://en.wikipedia.org/wiki/Music_Genome_Project?wprov=sfl...
I wish other music apps could license their recommendation system. Still nothing seems to come close.
In my personal experience I gave up on Pandora. It was regularly suggesting me music that wasn't at all similar to the song I started on. In fact it was consistently worse at finding me similar music than just plain Spotify radio (or playlist enhancer) and/or YouTube Music radio.
Haha, same. I used to work in a music equipment rental warehouse that was staffed by musicians and all day we would be curating and training our favorite Pandora stations. If a bad song came on the person closest to the computer would scan the warehouse to see how many of us were giving that song a thumbs-up or a thumbs-down and train the algorithm according to our votes.
The trouble was, despite our diligent training and curation of many Pandora stations, any station remotely related to rock would eventually converge on Morrissey. It got so bad that whenever a Morrissey song would play you could hear shouts of protest from across the warehouse and it would be immediately downvoted with extreme prejudice.
Nevertheless it would keep feeding us Morrissey so the joke among us became “All stations lead to Morrissey”.
I feel like many (most?) people who used Pandora extensively have a similar story, although curiously it never seems to be the same band. My fixed point was Radiohead's Karma Police, specifically. I wonder if your personal Pandora fixed point says something about you...
To be very fair, there's nothing plain whatsoever about Spotify's recommendations. Not only do they have the largest corpus of training data, their models are hard to beat.
I wish they had a way for me to say I'm not interested in something as well. For years there's been a few of the same albums recommended to me every day. Like, I've ignored them for this long and it's clear I'm not interested but the space for things I might actually listen to is still being wasted.
What's worse is that they're not even obscure albums. Like, if I was ever going to get into the Eagles I would have already done so, I don't need to "discover" them.
It was actually the other way around. It would play me songs technically within the same broad genre (Hip Hop, RnB, Pop) but wildly different sound.
It felt less like a music genome project and more like this typical nonsense streaming platforms do, "people who listen to song A, also tend to listen to song B".
Yes, so amazingly labor-intensive. Now I have found some programs which boast of a feeble seventy percent accuracy in identifying the key of a song (if you were going to use the Camelot System to build a mix).
Hm... I never thought that would be extremely useful but I think I have that working close to perfection on piano (I need it for audio->midi->score conversion), I should probably try it on other styles of music as well.
So, I am told -- and could be wrong -- that the subtle art of DJing requires many little tricks in tandem. Some are obvious, like similar tempos, similar "energy" (I have never heard a definition of this I could understand). Also, from one song to another, you're only supposed to move either major to minor, minor to major, or change just one letter. That's known as the Camelot method and it may be a lot of hot air.
Another trick I heard was taught in schools was "don't tickle me with a feather and then hit me with a brick."
I wish other music apps could license their recommendation system. Still nothing seems to come close.