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Machine learning and the arts: A creative continuumSketch a doodle of a drum or a saxophone to conjure a multi-instrumental composition. Look into a webcam, speak, and watch your mouth go bouncing across the screen — the input for a series of charmingly clunky chain reactions.

This is what visitors to the MIT Lewis Music Library encounter when they interact with two new digital installations, “Doodle Tunes” and “Sounds from the Mouth,” created by 2022-23 Center for Art and Technology (CAST) Visiting Artist Andreas Refsgaard in collaboration with Music Technology and Digital Media Librarian Caleb Hall. The residency was initiated by Avery Boddie, Lewis Music Library department head, who recognized Refsgaard’s flair for revealing the playfulness of emerging technologies. The intricacies of coding and machine learning can seem daunting to newcomers, but Refsgaard’s practice as a creative coder, interaction designer, and educator seeks to open the field to all. Encompassing workshops, an artist talk, class visits, and an exhibition, the residency was infused with his unique sense of humor — a combination of lively eccentricity and easygoing relatability.
Learning through laughter

Refsgaard, who is based in Copenhagen, is a true maverick of machine learning. “I’m interested in the ways we can express ourselves through code,” he explains. “I like to make unconventional connections between inputs and outputs, with the computer serving as a translator — a tool might allow you to play music with your eyes, or it might generate a love poem from a photo of a burrito.” Refsgaard’s particular spin on innovation isn’t about directly solving problems or launching world-changing startups. Instead, he simply seeks to “poke at what can be done,” providing accessible open-source templates to prompt new creative ideas and applications.

Programmed by Refsgaard and featuring a custom set of sounds created by Hall, “Doodle Tunes” and “Sounds from the Mouth” demonstrate how original compositions can be generated through a mix of spontaneous human gestures and algorithmically produced outputs. In “Doodle Tunes,” a machine learning algorithm is trained on a dataset of drawings of different instruments: a piano, drums, bass guitar, or saxophone. When the user sketches one of these images on a touchscreen, a sound is generated; the more instruments you add, the more complex the composition. “Sounds from the Mouth” works through facial tracking and self-capturing images. When the participant faces a webcam and opens their mouth, an autonomous snapshot is created which bounces off the notes of a piano. To try the projects for yourself, scroll to the end of this article.

Libraries, unlimited

Saxophone squeals and digital drum beats aren’t the only sounds issuing from the areas where the projects are installed. “My office is close by,” says Hall. “So when I suddenly hear laughter, I know exactly what’s up.” This new sonic dimension of the Lewis Music Library fits with the ethos of the environment as a whole — designed as a campus hub for audio experimentation, the library was never intended to be wholly silent. Refsgaard’s residency exemplifies a new emphasis on progressive programming spearheaded by Boddie, as the strategy of the library shifts toward a focus on digital collections and music technology.

“In addition to serving as a space for quiet study and access to physical resources, we want the library to be a place where users congregate, collaborate, and explore together,” says Boddie. “This residency was very successful in that regard. Through the workshops, we were able to connect individuals from across the MIT community and their unique disciplines. We had people from the Sloan School of Management, from the Schwarzman College of Computing, from Music and Theater Arts, all working together, getting messy, creating tools that sometimes worked … and sometimes didn’t.”

Error and serendipity

The integration of error is a key quality of Refgaard’s work. Occasional glitches are part of the artistry, and they also serve to gently undermine the hype around AI; an algorithm is only as good as its dataset, and that set is inflected by human biases and oversights. During a public artist talk, “Machine Learning and the Arts,” audience members were initiated into Refsgaard’s offbeat artistic paradigm, presented with projects such as Booksby.ai (an online bookstore for AI-produced sci-fi novels), Is it FUNKY? (an attempt to distinguish between “fun” and “boring” images), and Eye Conductor (an interface to play music via eye movements and facial gestures). Glitches in the exhibit installations were frankly admitted (it’s true that “Doodle Tunes” occasionally mistakes a drawing of a saxophone for a squirrel), and Refsgaard encouraged audience members to suggest potential improvements.

This open-minded attitude set the tone of the workshops “Art, Algorithms and Artificial Intelligence” and “Machine Learning for Interaction Designers,” intended to be suitable for newcomers as well as curious experts. Refsgaard’s visits to music technology classes explored the ways that human creativity could be amplified by machine learning, and how to navigate the sliding scale between artistic intention and unexpected outcomes. “As I see it, success is when participants engage with the material and come up with new ideas. The first step of learning is to understand what is being taught — the next is to apply that understanding in ways that the teacher couldn’t have foreseen.”

Uncertainty and opportunity

Refsgaard’s work exemplifies some of the core values and questions central to the evolution of MIT Libraries — issues of digitization, computation, and open access. By choosing to make his lighthearted demos freely accessible, he renounces ownership of his ideas; a machine learning model might serve as a learning device for a student, and it might equally be monetized by a corporation. For Refsgaard, play is a way of engaging with the ethical implications of emerging technologies, and Hall found himself grappling with these questions in the process of creating the sounds for the two installations. “If I wrote the sound samples, but someone else arranged them as a composition, then who owns the music? Or does the AI own the music? It’s an incredibly interesting time to be working in music technology; we’re entering into unknown territory.”

For Refsgaard, uncertainty is the secret sauce of his algorithmic artistry. “I like to make things where I’m surprised by the end result,” he says. “I’m seeking that sweet spot between something familiar and something unexpected.” As he explains, too much surprise simply amounts to noise, but there’s something joyful in the possibility that a machine might mistake a saxophone for a squirrel. The task of a creative coder is to continually tune the relationship between human and machine capabilities — to find and follow the music.

“Doodle Tunes” and “Sounds from the Mouth” are on display in the MIT Lewis Music Library (14E-109) until Dec. 20. Click the links to interact with the projects online.

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Augmented Sixth Chords, As Digested By A Jazz Musician. Tonal Harmony TutorialToday we’re going to talk about this chord:

Nowadays we see this chord as a subV/V, but in the Classical period this chord was treated using a very different perspective. Composers back then, saw this chord as an augmented sixth chord.

Watch the entire lesson here

Although these two points of view are very different, the reason for using this chord was the same back then as it is now: to tonicize the V chord — in what we call: a Half Cadence.

For those of you studying tonal harmony, I think this will clarify how, and why, this chord works, and how to solve those challenging tonal Harmony worksheets that your teacher always seems to be giving you.

For jazz musicians this is just a subV/V. When you play it on the piano, it’s clearly a dominant chord. And there’s three variations: the German augmented sixth (with all of the regular notes), the Italian augmented sixth (which has no 5th), and the crazy French augmented sixth version (with a b5).

Now, in the classical era, they didn’t see this chord as a dominant chord — made out of the 1 3 5 and b7. Here’s how this chord works for the classical mind…

This concept was developed from the perspective of being in a minor key. It works perfectly fine in a major key, but the augmented sixth chord was conceived from the perspective of being in minor.

So let’s say we’re in the key of C minor.

What’s the V of C? G! Now, what is the best trick to tonicize that G? Well, if we use the Ab (only a half step above G), and an F# (which is the leading tone to G), when we write it down, we have an augmented sixth, which resolves to that G in octaves by contrary motion.

Remember this: the augmented six chord always resolves to the V of the key in octaves (or doubled unison, if we’re using an inversion of the augmented sixth chord).

But an augmented sixth is nothing else than a b7. Ab to F# is the same as Ab to Gb. If we now add the 3rd of the chord, we get an Ab7 dominant chord without the 5th. And this C wants to go to the 3rd of the G chord like this… This is the Italian augmented sixth chord.

If we also add the 5th of the chord (Eb) we get the German augmented sixth. And of course Eb wants to go to a D (the 5th of the G chord)

So now, we have a beautiful tension-release effect. These two notes resolve in contrary motion. By the way, in the Italian sixth we can double the 3rd of the chord — since we don’t have the Eb — and then, one C moves down to the B, and the other moves up to the D.

But what if the Eb is already resolved to the D? That’s the French augmented sixth.

The D is already present in the augmented sixth chord. It doesn’t have to move at all.

So now, when you see a problem like this…

…just think like this:

The Ab wants to move down a half step. So it goes to G, which must be the 5th of the key. And the G is the V in the key of C minor. So we’re in the key of C minor. We’re going to resolve the G’s in octaves. So the top note has to be a leading tone to G (F#). And there’s your augmented sixth (Ab to F#)

And we add the 3rd of the chord (C) which by the way, is always the tonic of the key that we’re in. And to make it a French augmented sixth, we have to add a D — which is the 5th of the G chord — already resolved in the chord. This D is actually the b5 of our Ab chord.

So once you understand the purpose of this chord, and how it works, it’s very easy to solve this problem.

Let’s do another one.

This Eb will move down to D. D is the V in our key, then we’re in the key of G minor. And the other D — an octave above — should be approached by its leading tone (C#)

Then we add the 3rd of the chord, which is our tonic, and since it says that it’s an Italian augmented sixth, we just double it. I’m going to go ahead and put it an octave higher in the upper voice. Now, one G moves down to F#, and the other moves up to A. A nice D chord.

Let’s do a German augmented sixth.

So, F has to move down to E, right? Then, E is the V of our key, which means we’re in A minor. Now we have to add the leading tone to E — which is D#. Now we add the 3rd (A) and the 5th (C). So this chord is the German augmented sixth in the key of A minor, and look: it’s an F7! It just looks weird when we write it down like this, and of course, it resolves to an E chord like this…

And remember, this is just a substitute of the V/V — on the opposite side of our circle. This German augmented sixth, in the key of A minor, is just an F7 that is replacing the B7 — the five of E.

I think it’s super interesting how harmony has its roots in counterpoint. Nowadays we would never write an F7 chord like this but, should we?

If you want to get access to this (and many other) pdf worksheets with all sorts of music related topics, you can join our “Exclusive Access” membership on YouTube here: https://www.youtube.com/channel/UCBCch4Wd-JAuyURvmmA1oyQ/join

And you can check out download Mapping Tonal Harmony Pro which is the app I used to present the video.