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MusicXML

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Re: MusicXML

#21

Post by adrianh »

saltminer wrote: post #19
adrianh wrote: post #15

Earlier quoted context omitted.

This is a common complaint, and it's something we're trying to remedy with MNX: https://w3c.github.io/mnx/docs/ Music notation is incredibly complex, and there are many places things can go wrong. There's a wide spectrum of error situations, such as: * The exporting application "thinks" about notation in a different way than the importing application (i.e., it has a different mental model). * MusicXML provides multip…

> MusicXML provides multiple ways of encoding the same musical concept, and some applications don't take the effort to check for all possible scenarios. This sounded interesting, so I went to the webpage, and found this point specifically called out: > It prioritizes interchange, meaning: it can be generated unambiguously, it can be parsed unambiguously, it favors one-and-only-one way to express concepts, and multipl…

Thanks, that's good feedback — will add that to the to-do list.

Just to give you a quick response: look into MusicXML's concept of a "cursor". Parsing a MusicXML document requires you to keep an internal state of a "position", which increments for every note (well, careful, not every note -- not the ones that contain a "chord" subelement!) and can be explicitly moved via the "backup" and "forward" elements: https://w3c.github.io/musicxml/musicxml-reference/elements/f...

For music with multiple voices, this gets easy to mess up. It's also prone to fractional errors in music with tuplets, because sometimes software chooses to use MusicXML position numbers that aren't evenly divisible into the rhythms used in a particular piece of music. That can result in a situation where the MusicXML cursor gets to a state that doesn't actually align with any of the music.

Re: MusicXML

#22

Post by gnulinux »

Tokkemon wrote: post #8

I work for Sibelius so I'm heavily involved in this world. MusicXML is a great standard and offered a solid basis for data interchange between music notation programs. But now there's a new group working to build a successor standard, MNX: https://w3c.github.io/mnx/docs/ It was originally going to be in XML but they recently switched to JSON, which is a good move, I think. I can't wait for it to be adopted as it will…

How about MEI?

https://music-encoding.org/about/

This is what MuseScore 4 will soon start using.

Re: MusicXML

#23

Post by zozbot234 »

gnulinux wrote: post #20
zozbot234 wrote: post #13

Earlier quoted context omitted.

Note that MIDI is a lot more effective when it comes to ML/AI, since it's multiple orders of magnitude less data. Daniel D. Johnson's (formerly known as Hexahedria, hired by Google Brain) model biaxial-rnn-music-composition is from 2015, requires very few resources for training or inference, and still delivers compelling, SOTA-or-close results wrt. improvising ("noodling") classical piano. https://github.com/danieldj…

MIDI is absolutely horrible for ML. It lacks very necessary information such as articulation etc which are important to make sense of music. It's popular because it's simple but there is no way to understand music by just looking at MIDI. I'm a hobbyist in this space (am a composer myself as well a software engineer) and currently all tools are very poor. MusicXML is better than MIDI. MEI [1] is better than MusicXML…

> MIDI is absolutely horrible for ML.

It depends what you're trying to do. If you're trying to generate sheet music that's pretty to look at and easily understandable to a performer, then yes obviously it's not enough. If you want notes that will actually sound good when played back, it's hard to beat it.

Re: MusicXML

#24

Post by odyssey7 »

adrianh wrote: post #16
odyssey7 wrote: post #14

Earlier quoted context omitted.

How would you explain the relationship between MNX and SMuFL?

They're totally different things, though the standards are maintained by the same people. SMuFL is a font layout specification. It solves the longtime problem of "I'm making a music font. Which Unicode code glyph should I use for a treble clef?" For many years, this was a Wild West situation, and it wasn't possible to swap music fonts because they defined their glyphs in inconsistent ways. This problem is basically s…

Thanks. If it isn't too many questions, are any layout concerns encodable in MNX, or is it scoped to semantic information only?

Re: MusicXML

#25

Post by gnulinux »

zozbot234 wrote: post #23
gnulinux wrote: post #20

Earlier quoted context omitted.

MIDI is absolutely horrible for ML. It lacks very necessary information such as articulation etc which are important to make sense of music. It's popular because it's simple but there is no way to understand music by just looking at MIDI. I'm a hobbyist in this space (am a composer myself as well a software engineer) and currently all tools are very poor. MusicXML is better than MIDI. MEI [1] is better than MusicXML…

> MIDI is absolutely horrible for ML. It depends what you're trying to do. If you're trying to generate sheet music that's pretty to look at and easily understandable to a performer, then yes obviously it's not enough. If you want notes that will actually sound good when played back, it's hard to beat it.

> If you want notes that will actually sound good when played back, it's hard to beat it.

I strongly disagree with this. There is no good algorithmic music generator trained on MIDI. They all generate elevator music.

Re: MusicXML

#26

Post by zozbot234 »

gnulinux wrote: post #25
zozbot234 wrote: post #23

Earlier quoted context omitted.

> MIDI is absolutely horrible for ML. It depends what you're trying to do. If you're trying to generate sheet music that's pretty to look at and easily understandable to a performer, then yes obviously it's not enough. If you want notes that will actually sound good when played back, it's hard to beat it.

> If you want notes that will actually sound good when played back, it's hard to beat it. I strongly disagree with this. There is no good algorithmic music generator trained on MIDI. They all generate elevator music.

Are you aware of the system I linked above? D.D. Johnson has a blogpost https://www.danieldjohnson.com/2015/08/03/composing-music-wi... with plenty of examples of what an instance of his model can generate. It may not be all that "good" in an absolute sense, but it's at least musically interesting, the opposite of elevator music. (There's also a proprietary model/AI called AIVA about which very little is known, but it does seem to be bona-fide AI output - albeit released in versions that have been orchestrated by humans - based on what it sounds like.)

Re: MusicXML

#27

Post by jsphweid »

treyd wrote: post #6
1-6 wrote: post #4

Seems like MusicXML is a great format for ML applications. You need to start somewhere and machine-readable code is important.

MusicXML seems to be more for notation and sheet music typesetting rather than algorithmic operations on the notes themselves. Sure you could train a model on it but you'd be better off doing it on the specific domain and classically translating up to the XML format.

Right, but sheet music is ubiquitous in countless musical contexts and there's very little attention to it from the ML side. Sheet music is somewhat arduous to create and there is definitely room for a lot of automation and ML could help out a lot. I experimented with a tokenizer / GPT-2 (decoder-only) model for MusicXML (https://github.com/jsphweid/xamil) that is able to generate single staff music somewhat coherently. But it's just a first step and I don't care about generating (EDIT: hallucinated) music. Ideally we could add an encoder part to a model like this that takes in MIDI tokens and spits out sheet music. But I haven't gotten that far and don't have the ML chops to do it at this time. But it shouldn't be impossible.

Re: MusicXML

#28

Post by im3w1l »

jonathrg wrote: post #7

I have not had much success using MusicXML to switch between different notation programs. Trying to read a score exported from Musescore as MusicXML in Sibelius or vice versa feels worse than switching between Microsoft Office and other ostensibly compatible formats. Does anyone have any success stories?

I recently used a funny workflow involving MusicXML. I wanted to learn a song that I only had sheet music for and not being much of a sightsinger, I had manually input the sheet music into Vocaloid so I could sing along with it (OCR exists but in my experience is in such a sorry state and requires so many manual fix ups that for the moment it's easier to type it in manually. As for enterring the data I have experimented and I'm significantly faster and more accurate with a piano roll than typing note names in musescore).

Now as this song had nonsense lyrics and many repetitions and almost-repetitions, the structure of the song didn't quite pop out to me, so what I did was export a midi from vocaloid that I opened musescore. From musescore I then exported it as MusicXML. I opened that in Notepad++ for the sole purpose of pretty printing the xml to normalize the texual representation and saved it right back. I took that and opened it in a jupyter notebook where I scraped it for elements with regular expressions and then I searched for repeating ones, that I assembled into repeating segments and sub-segments.

This helped me memorize the song.

What I liked about MusicXML was that it was self-documenting enough that I didn't need to reference documentation and I could find candidates for normalization quite easy (for instance I didn't care about directions of stems or inferred dynamics).

A gotcha is that Musescore 4 has a bug where it doesn't show the "midi import" where you can adjust the duration quantization, this didn't matter to me for this song, but I did bite me once in the past when opening a midi from Vocaloid. Musescore 3 works. Without playing around with that there can be an issue where it infers 16th notes as staccato 8th notes and similar.

Re: MusicXML

#29

Post by adgjlsfhk1 »

jsphweid wrote: post #27
treyd wrote: post #6

Earlier quoted context omitted.

MusicXML seems to be more for notation and sheet music typesetting rather than algorithmic operations on the notes themselves. Sure you could train a model on it but you'd be better off doing it on the specific domain and classically translating up to the XML format.

Right, but sheet music is ubiquitous in countless musical contexts and there's very little attention to it from the ML side. Sheet music is somewhat arduous to create and there is definitely room for a lot of automation and ML could help out a lot. I experimented with a tokenizer / GPT-2 (decoder-only) model for MusicXML ( https://github.com/jsphweid/xamil ) that is able to generate single staff music somewhat cohere…

Having an MP3 to sheet music would be even better, but probably 10x harder to do well.

Re: MusicXML

#30

Post by account-5 »

Tokkemon wrote: post #8

I work for Sibelius so I'm heavily involved in this world. MusicXML is a great standard and offered a solid basis for data interchange between music notation programs. But now there's a new group working to build a successor standard, MNX: https://w3c.github.io/mnx/docs/ It was originally going to be in XML but they recently switched to JSON, which is a good move, I think. I can't wait for it to be adopted as it will…

Never heard of either before but having looked at the comparison [0] I think I prefer the XML version.

[0] https://w3c.github.io/mnx/docs/comparisons/musicxml/

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