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Agreed, although I generally think in terms of "obeying traditional music theory (to some extent) is necessary but not sufficient for a listenable melody". This

Agreed, although I generally think in terms of "obeying traditional music theory (to some extent) is necessary but not sufficient for a listenable melody". This also changes depending on genre and era - one reason for targeting early Western music, such as early two or 3 voice counterpoint is that composition was more regular and in accordance with theory (which was kind of codified after the fact, focused on explaining these types of composition), though the "reward problem" remains. Coming around to free jazz or extremely "modern" composition means violation of most or all rules while still being "musical" (at least to fans of those genres) - that is going to be even tougher and we are pretty far from automated generation of long multi-part composition without some extra hints from theory built into the models and data, even for music that closely follows theory. This is one reason many people in the space are focused on new tools for creators, instead of "automated creation" - what is "cool/interesting/listenable" is ill-defined, but making something which allows creators to explore the sonic landscape in really different ways seems a lot more plausible to me - more "weird synthesizers with neural networks" than "robo-artists".

TheOtherHobbes 9y ago
Theory turns out to be nowhere close to sufficient for defining musicality. If you write a rule-based counterpoint solver - this has been done, with varying levels of success - you'll find that not only do you have to include an extra set of rules that aren't defined in any of the standard texts, but that the best output you can expect is musically mediocre. The other approach is to create a patchwork of idiomatic cliches. That usually sounds more convincing, but still isn't musically interesting. And you can usually hear where the edges are glued together. It turns out that there is no theory of "good" music. It literally doesn't exist. All the standard texts for each style - and it doesn't matter which style you pick, from Palestrina to pop - are very incomplete guides that rely on human intelligence and creativity to fill in the gaps. Throwing neural networks at this problem doesn't make it any easier, because no one knows what to look for. Features in artistic style transfer are easy to parse - shape, texture, and that's pretty much it, all packaged in a ready-to-go 2D distribution. What are the musical features that define not just one possible musical style, but all of them, and would allow anyone to morph smoothly from Wagner to Taylor Swift to Balinese Gamelan to DubStep?
- kastnerkyle 9y ago
  On rule based solvers - this is true if you simply stop at "be within the rules" and do strict constraint solving ala the coloring problem. I think there is potential to do something by blending all 3 (rules and constraint checking, rewards (perhaps based on idioms, riffs, and cliches), and some additional discriminator/critic/metric learning) if you narrow the criteria sufficiently (3 voice counterpoint in the style of Josquin de Prez for example). I would really be pleased to see something that can fill out "theory 101" counterpoint worksheets against a cantus firmus, even if the results would be poorly graded on "style" it is someplace to start getting feedback and collecting data to try and quantify that it factor for a narrow narrow subsection of the wide world of music.

TheOtherHobbes 9y ago

Theory turns out to be nowhere close to sufficient for defining musicality. If you write a rule-based counterpoint solver - this has been done, with varying levels of success - you'll find that not only do you have to include an extra set of rules that aren't defined in any of the standard texts, but that the best output you can expect is musically mediocre. The other approach is to create a patchwork of idiomatic cliches. That usually sounds more convincing, but still isn't musically interesting. And you can usually hear where the edges are glued together. It turns out that there is no theory of "good" music. It literally doesn't exist. All the standard texts for each style - and it doesn't matter which style you pick, from Palestrina to pop - are very incomplete guides that rely on human intelligence and creativity to fill in the gaps. Throwing neural networks at this problem doesn't make it any easier, because no one knows what to look for. Features in artistic style transfer are easy to parse - shape, texture, and that's pretty much it, all packaged in a ready-to-go 2D distribution. What are the musical features that define not just one possible musical style, but all of them, and would allow anyone to morph smoothly from Wagner to Taylor Swift to Balinese Gamelan to DubStep?

kastnerkyle 9y ago
On rule based solvers - this is true if you simply stop at "be within the rules" and do strict constraint solving ala the coloring problem. I think there is potential to do something by blending all 3 (rules and constraint checking, rewards (perhaps based on idioms, riffs, and cliches), and some additional discriminator/critic/metric learning) if you narrow the criteria sufficiently (3 voice counterpoint in the style of Josquin de Prez for example). I would really be pleased to see something that can fill out "theory 101" counterpoint worksheets against a cantus firmus, even if the results would be poorly graded on "style" it is someplace to start getting feedback and collecting data to try and quantify that it factor for a narrow narrow subsection of the wide world of music.