The idea is that the brain finds it pleasing to learn things. It effectively seeks novelty. Repetitive, predictable music does not sound pleasing. Pure randomness also does not sound pleasing. Somewhere in between is novelty. Patterns that are definitely real, but new. That somehow violate your brains expectations.
The ability to enjoy music is related to how good the high-dimensional reconstruction is. A listener who has no experience with a genre might not perceive subtle symmetries and higher order patterns, thus, it's just some kind of noise. The more she listens, the more her musical "vocabulary" and ability to perceive these symmetries increase. Developing taste for it is developing ability to represent it fully as it is, a form of integrated information.
Blues has a fairly strict formula in which most songs follow. Most songs are in 4/4, and most modern music sounds fairly similar yet people are really into it.
(BTW, I believe we're overly simplifying by speaking of music as a single entity. All of the elements you mentioned are a foundation in more popular music, but good luck finding them in more modern or experimental genres.)
The cognitive effort to digest Schoenberg is different from that for a pop song. Still, you can progressively familiarize yourself with a genre, and relax on pieces that seemed hard and inaccessible earlier.
Yes, as a passionate music collector and someone that can get lost in weird, obscure and very leftfield music, this is something I notice all the time. You start with something accessible only to find yourself enjoying obscure 70s synth funk recorded on tape in someone's bedroom months/years later. Or similar.
It's why we recommend "Kind of blue" whenever someone wants to get into Jazz, which is difficult if you just randomly start...anywhere.
The mere score of a blue piece is just as good as useless for conveying the power of a particular blues performance for example.
Most 12-bar blues use a similar chord progression but have different melodies. Even the same song performed by two different musicians will sound different enough to be perceived as "novel".
Israel Kamakawiwo'ole has similar vocal attributes, also very enjoyable.
Pop music is repetitive and predictable, yet, ... well, enough said there.
Just because we can transcribe an audio recording into 12 tones, and 16 divisions of a bar, doesn't mean that's all the information it contains. There's a whole lot more.
There's little variations in pitch, tone, dynamics, etc. All the stuff that separates a great recording from a lifeless snooze.
My theory is that pleasing music falls half way been the predictable, and the unpredictable. So if the beat is too predictable, the artist can always compensate by using an unusual melody... etc. But many of the ways an artist can add unpredictability can't be expressed with traditional notation.
I'm a "lover of serious music" and I do have some favorite albums that I come back to every now and then. But I don't listen to the same song in a constant loop on repeat. That would be dreadfully boring.
Similarly, most people would not enjoy a song consisting solely of a single measure repeated verbatim over and over again. Even the most repetitive music has some variation.
On a more serious note -- yes, but even this would become boring quickly despite the variations. This problem has been solved by:
- using different themes for different sections, or
- intertwining two or more such themes for contrast within the same section.
Prime examples of this approach are Beethoven piano sonatas.
I seem to recall I read somewhere that (part of?) the album was painstakingly made using Supercollider , but can't find a proper reference.
Indeed, even subtle variation can be enough to turn something "musical".
I play music, which requires listening to yourself practice the same things over and over again. Sometimes just a couple of bars. I like it.
Even if you get bored, that is not the same thing as the music suddenly sounding "bad". It sounds exactly the same.
But when you are practicing, you rarely play it exactly the same each time. Otherwise, what's the point of practicing? Hopefully, it sounds a bit better every time you go through it.
http://www.nature.com/nature/journal/vaop/ncurrent/full/natu... ("Indifference to dissonance in native Amazonians reveals cultural variation in music perception")
Actually I find it remarkable how unmusical it sounds- when studying music theory there are often very simple rules you're mostly meant to follow, yet I've never heard any computer generated music that sounds even close to passable. It seems surprising to me, I would have thought it would be easier.
Which is exactly how computer generated music sounds to me. Pleasant enough, superficially, but with no real content.
Human-generated music uses repetition a lot. If not in the melody, at least in the harmonic progression or rhythm.
This algorithm doesn't seem to attempt anything like thematic development or rhythmic drive.
I wonder how it would sound if, instead of looking ahead only one chord, the algorithm instead generates randomly up to a certain period, then repeats what it just played with some slight perturbations.
In particular, the passage beginning:
"Can music exist without repetition? Well, music is not a natural object and composers are free to flout any tendency that it seems to exhibit. Indeed, over the past century, a number of composers expressly began to avoid repetitiveness in their work...."
The authors of the piece found that both amateur and highly knowledgeable listeners thought that modified versions of some pieces, in which repetition had been injected, were more persuasively musical.
And the larger point is the very deep relationship between repetition and music.
Granted, I wouldn't say it's song of the year or anything, but it's definitely listenable. Does anyone know of his general approach in his software for writing music?
Core elements are often cliched, but getting from a cliched chord sequence to a complete piece/song that captures the imagination of listeners is very much harder than it looks.
I've seen an expert systems for generating counterpoint that used a grammar with more than a hundred separate production rules, and still failed to generate interesting bass lines.
Interesting music is extremely non-trivial. Conversely, trivial algos used in trivial ways reliably produce trivial output.
Tastefully. That's the biggest problem with computers.
If we had a magical black box oracle that could tell us that variation A is "5 good" and variation B is "5.5 good", then that would be sufficient to implement a system that makes a lot of great art. But we don't, and possibly can't without strong AI or something like that.
IIRC the samples sounded good to me, but I have been unable to play them now to refresh my memory.
Track 1: https://www.youtube.com/watch?v=QEjdiE0AoCU
Here's the first CD produced: https://youtu.be/A9XCexln6xY?list=PLUSRfoOcUe4a-4pXqqET9DkPn...
Agreed. Though truly breakthrough music is often about knowing when and how to break those rules. Some of the most timeless songs are the ones where the artist made an unexpected deviation that bent the rules in just the right way. It's something that only the very talented can pull off without doing so by accident.
But overall, isn't this saying that removing the randomness and applying known music theory is what makes music sound musical? Is there any insight that using the computer is uncovering?
Randomness produces too much motion, and also fails to establish pattern or theme. A set of random major chords still sounds very random, it doesn't progress and leaves the listener unsatisfied. So many attempts at computer music start from randomness and the proceed to remove it little by little with structured rules -- maybe starting from randomness isn't the right place to start?
Had a tiny epiphany about randomness recently when I edited a video with still photos in it and applied my computer's "Ken Burns" effect, where it zooms & pans slowly. The automatic version picks random start and end points, fairly close together, and the movement is slow and gentle. But I watched it and noticed it was very unfocused and adding unharmonious motion. Ken Burns is telling stories with his pans & zooms - zooming in to highlight a specific face he's talking about, or panning over to reveal a place. It was a pain to re-edit the video manually, and hand-animate every pan & zoom, but when I was done, I was completely shocked how much less motion there was, like an order of magnitude less movement. The randomness had just scattered everything and didn't go anywhere. That's what I'm hearing in these musical examples - Brownian motion - too much movement that doesn't go anywhere.
This is like generating sentences with statistical autocomplete. For a few words, the phrases sort of make sense, but that illusion disappears with more length. More high-level structure is needed.
Somebody will probably figure this out soon using deep learning and grind out background music for movies. Oh, right. (Juke-bot may be a hoax.)
A lot in music breaks down to establishing patterns and breaking them. Simpler music, like pop music relies heavily on well known patterns, but at least the chorus usually has some element of surprise within the song.
My theory is, that people like music that is just a little (or for the more adventurous a little more) surprising.
With training in listening to music, as a musician or just as an ambitious listener, your taste will begin to widen to more complex music. This is because you begin to recognize its patterns (and only when a pattern establishes, you can break it to create suspense or surprise). Simpler stuff will become very shallow, because it's so predictable (just remember the shameful musical taste when coming of age).
Of course there is more to a pop song than harmony and melody, so even when your taste becomes more sophisticated you might like a pop song for its emotional appeal or some subtile complexity or depth the novice won't even notice.
Listening to good music (as a non-musician) is for me mostly about experience emotions.
Listening to this music leads immediately to be about identifying what rules the generator was programmed to follow. The stricter the rules (less random), the more music-like it may sound, but without any emotion. Except maybe comedy.
This is a cool demo, although I suppose it shows a bit more where the basic texture of western music comes from than songwriting. But what I find most interesting about his ideas is how he's able to fairly convincingly connect them to the entire western music tradition.
 http://dmitri.tymoczko.com/geometry-of-music.html (there's a link to Amazon from that page)
But, of course, it has nothing to do with harmonic series and other man-made concepts of the mind.
I'd like to read more without really diving into music theory too far.
It won't tell you how to write a song, but it'll start you with a solid foundation for music production. You can start by just finding loops and samples online and putting tracks together that way. Then you can start replacing bits with original music. Think of it like learning how to program by cutting and pasting code from stack exchange.
My only complaint is that the audio playback has annoying zero-crossing pops.
1) Lessons or books on how to play a specific instrument. The good ones will cover the most relevant basics of music theory--stuff like chords, scales, keys, and voice leading.
2) Learning how to play your favorite songs. Copying performances and then experimenting with variations on them is essential for getting an intuitive sense of how it all works.
The author covers lots of ground this algorithm seems to ignore. I wonder what sort of music a program that used these suggestions could make.
That may seem disconnected from the sounding good part but it's what gives you a core to build on. You can take the thought and express it in a very simple, low-fi, minimalist way, or go all out and build a huge arrangement and smother it in production. That's something that is better to decide upon by design than by trial and error.
Given your instrument choice you might also be very well served by the "Music Theory / Harmony / ... for Computer Musicians" series by Michael Hewitt.
i thought the last clip was actually enjoyable, the busy clattering noisy one with the effects and the variety of instrument sounds. there's plenty of weird electronic music i listen to that's in that ballpark at times.
these clips would all make fine sample fodder.
i appreciate the attempted disclaimer at the end ('That is, "good" to typical Western listeners'). but i think a lot of typical western listeners don't realize how much things like texture (timbre, whatever) and other sorts of things not easily captured by western classical music notation matter to them. for instance, a lot of what makes old jazz sound like old jazz is that great warm scratchy sound that the recording technology of the time necessarily imprinted on the original recordings. likewise, if you scored autechre or aphex twin and got an orchestra to play it, it might sound interesting or enjoyable, but it wouldn't sound anything like autechre or aphex twin. and of course, the intonation and cadence and syllable stretching of well delivered rap vocals or well executed vocal sample chopping is nothing if not musical, but those things aren't easily transcribed by the notation in question here either. but those are all things regularly enjoyed by a wide swath of western listeners. so i think the disclaimer should be more like 'That is, "good" to the Western classical music establishment.'