Roon 1.4 - Radio Feedback

Nope. That’s not what documentation is for.

It’s not a very good idea for anyone but the developers/product people working on Radio to develop deep intuition about what it’s doing under the hood. It’s an area of active development/change, and will continue to be indefinitely. If you build precise expectations about it, they will be broken, probably soon.

That is a reason why we are not going into deep explanations here about the underlying implementation, and also why we are not going to “bare the guts” of the algorithm to a bunch of sliders and make it tweak-able. The actual knobs on the inside would not make a good product or user interface, and they change too often to be a stable target for that anyways.

Another thing that’s super important to understand about “Radio 1.4” is that it represents only about 15-20% of our actual Radio project. Internally, I actually call what you guys are using now “offline mode radio”, since that’s how it fits into the bigger picture. I call it that because what you’re using right now is the algorithm that–in the future–Roon will use to do radio within the library when no internet connection is available.

“Radio 2.0”–the whole thing, not just this small piece of it–is intended to be a proper modern radio feature–radio that utilizes information about all of the content on Earth, not just your library, a la Spotify, Pandora, etc.

At this point in time, it’s not possible to do radio properly without relying on large data sets in the cloud. Yes, I know some people back in 2008 did cool stuff within a local library (Mirage, MusicIP, …), but we would be fools to place a big bet on such a narrow-minded approach in 2018. The world has moved on to larger scale implementations for this, and we must too.

These radio systems are complex and multi-faceted. To work right, they must combine aspects of metadata similarity, auditory similarity, mood/style analysis, usage-based relationships, while leveraging explicit and implicit feedback. More than one of these areas involve machine learning and working with data at scale. Different people in this thread have identified some of these aspects, but they are all just ingredients. Work on the larger-scale project is underway, of course.

This period we are in today, where we are relying on “offline mode radio” for everything, is an opportunity to work out the kinks for offline mode and make it as good as possible within the design constraints, so we welcome your feedback, and will continue to iterate on it.

As for the current radio feature–there has already been one iteration on this feature released to the public in January, and second iteration is entering alpha testing soon. These ideas are being applied to the larger-scale system as it’s worked on as well, so hopefully we won’t see these same issues reappearing down the road when we turn on the bigger feature.

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