I really want to understand how Valence works. I’m assuming that’s the recommendation model that powers the ‘start radio’ on tracks as well the ‘keep playing’ when the queue is empty.
The generic stuff on the website doesn’t help. I’m hoping by better knowing how it works I maybe can direct it better
I’ve found for music that belongs to a well listened genre then it seems to work well. Eg I can play some Bowie it’ll carry on well.
However for music very few people may listen to on Roon it can’t seem to find any matches.
Also on the radio it seems to loose track of first song on which the radio started from ie when my queue finished. Eg I was playing some Brit funk and it went into some soul then a house music track then to some acoustic. It was pleasing (it’s was flicking my library mostly) but completely off the track/vibe of music I expected it to carry on.
Again would be great to hear a technical working of it hopefully from the devs.
Roon Valence is a cloud-based data and machine-learning engine that powers music discovery, recommendations, and library organization within Roon. It combines deep, authoritative commercial metadata with listening habits from over 100,000 expert Roon users to map complex relationships between artists, composers, genres, and performances. This system acts behind the scenes to drive features like Roon Radio, intelligent search, and personalized recommendations tailored to your unique taste.
Thanks I read that but that doesn’t really give me clues to why so many songs I have often end up with ‘nothing similar found’.
Maybe it’s with ‘commercial metadata’ how up to date is that when used in Valence. or is the other users in Roon listening to similar/related tracks that really matters - in which is there too much bias to the x number of Roon users listening preferences?
Why does this always remind me of the famous quote from the Hitchhikers Guide To the Galaxy regarding a Tea making machine…?
He had found a Nutri-Matic machine which had provided him with a plastic cup filled with a liquid that was almost, but not quite, entirely unlike tea. The way it functioned was very interesting. When the Drink button was pressed it made an instant but highly detailed examination of the subject’s taste buds, a spectroscopic analysis of the subject’s metabolism and then sent tiny experimental signals down the neural pathways to the taste centers of the subject’s brain to see what was likely to go down well. However, no one knew quite why it did this because it invariable delivered a cupful of liquid that was almost, but not quite, entirely unlike tea…
