Meet AI, the music composer who helped complete Beethoven’s incomplete 10th Symphony

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When Ludwig van Beethoven died in 1827, he was three years from the completion of his Ninth Symphony, a work hailed by many as his magnum opus. He had started to work on his 10th Symphony but, due to the deterioration of his health, was not able to make much progress: he left only a few musical sketches.

Since then, Beethoven fans and musicologists have been perplexed and complained about what could have been. His notes made fun of a magnificent reward, even if it seemed forever out of reach.

Now, thanks to the work of a team of music historians, musicologists, composers and computer scientists, Beethoven’s vision will come to life.

I chaired the artificial intelligence portion of the project, leading a group of scientists from creative AI startup Playform AI who taught a machine both all of Beethoven’s work and his creative process.

A full recording of Beethoven’s 10th Symphony is scheduled for release on October 9, 2021, the same day as the scheduled world premiere in Bonn, Germany, the culmination of an effort spanning more than two years.

Past attempts hit a wall

Around 1817, the Royal Philharmonic Society of London commissioned Beethoven to write his ninth and tenth symphonies. Written for an orchestra, symphonies often contain four movements: the first is performed at a fast tempo, the second at a slower tempo, the third at a medium or fast tempo, and the last at a fast tempo.

Beethoven completed his Ninth Symphony in 1824, which ends with the timeless “Ode to Joy”.

But when it comes to the 10th Symphony, Beethoven didn’t leave much behind except a few musical notes and a handful of ideas that he wrote down.

There have been some past attempts to reconstruct parts of Beethoven’s 10th Symphony. Most famous, in 1988, musicologist Barry Cooper ventured to complete the first and second movements. He woven together 250 bars of music from the skits to create what was, in his eyes, a production of the first movement that was true to Beethoven’s vision.

However, the rarity of Beethoven’s sketches prevented symphonic experts from going beyond this first movement.

Assemble the team

In early 2019, Dr Matthias Röder, director of the Karajan Institute, an organization in Salzburg, Austria that promotes music technology, contacted me. He explained that he was forming a team to complete Beethoven’s 10th Symphony on the occasion of the composer’s 250th birthday. Aware of my work on AI-generated art, he wanted to know if AI would be able to help fill in the blanks left by Beethoven.

The challenge seemed sizeable. To achieve this, the AI ​​would have to do something it had never done before. But I said I was going to give it a shot.

Röder then put together a team that included Austrian composer Walter Werzowa. Famous for writing Intel’s signature bong jingle, Werzowa was tasked with implementing a new type of composition that would integrate what Beethoven left behind with what AI would generate. Mark Gotham, an expert in computer music, led the effort to transcribe Beethoven’s sketches and process all of his work so that AI could be properly trained.

The team also included Robert Levin, a musicologist at Harvard University who also happens to be an incredible pianist. Levin had already completed a number of incomplete 18th century works by Mozart and Johann Sebastian Bach.

The project takes shape

In June 2019, the group reunited for a two-day workshop at the Harvard Music Library. In a large room with a piano, chalkboard, and a stack of Beethoven’s sketchbooks covering most of his known works, we explained how fragments can be turned into a complete piece of music and how AI can help. to solve this puzzle, while remaining faithful. to Beethoven’s process and vision.

Music experts in the room were eager to learn more about the kind of music AI has created in the past. I explained to them how the AI ​​had managed to generate music in the style of Bach. However, it was only a harmonization of an input melody that sounded like Bach. It didn’t come close to what we needed to do: build an entire symphony from a handful of phrases.

Meanwhile, the scientists in the room, including me, wanted to know more about the type of materials available and how the experts plan to use them to complete the symphony.

The task at hand finally crystallized. We would need to use full notes and compositions from all of Beethoven’s work, as well as the available sketches of the 10th Symphony, to create something that Beethoven himself could have written.

It was a huge challenge. We didn’t have a machine to which we could send sketches, push a button, and spit out a symphony. Most AIs available at the time couldn’t continue an unfinished piece of music beyond a few extra seconds.

We would need to push the boundaries of what creative AI could do by machine-teaching Beethoven’s creative process; how he took a few bars of music and meticulously developed them into moving symphonies, quartets and sonatas.

Reconstructing Beethoven’s Creative Process

As the project progressed, the human side and the machine side of the collaboration evolved. Werzowa, Gotham, Levin and Röder deciphered and transcribed the sketches of the 10th Symphony, trying to understand Beethoven’s intentions. Using his completed symphonies as a model, they attempted to piece together the puzzle of where the sketch fragments should go – what movement, what part of the movement.

They had to make decisions, like determining whether a sketch indicated the starting point of a scherzo, which is a very lively part of the symphony, usually in the third movement. Or they could determine that a line of music was probably the basis of a fugue, which is a melody created by interweaving parts that all echo a central theme.

The AI ​​side of the project, my side, found itself struggling with a series of difficult tasks.

First, and more fundamentally, we had to figure out how to take a short phrase, or even just a pattern, and use it to develop a longer, more complicated musical structure, just like Beethoven would have done. For example, the machine must have learned how Beethoven constructed the Fifth Symphony from a basic four-note motif.

Then, because the continuation of a phrase must also follow some musical form, whether it is a scherzo, a trio or a fugue, the AI ​​had to learn Beethoven’s process to develop these shapes.

The to-do list grew longer: we had to teach the AI ​​to take a melodic line and harmonize it. The AI ​​had to learn to connect two sections of music. And we realized that the AI ​​had to be able to compose a coda, which is a segment that ends part of a piece of music.

Finally, once we had a full composition, the AI ​​was going to have to figure out how to orchestrate it, which involves assigning different instruments for different parts.

And he had to accomplish these tasks the way Beethoven could.

Take the first big test

In November 2019, the team met again in person, this time in Bonn, at the Beethoven House Museum, where the composer was born and raised.

This meeting was the litmus test to see if AI could complete this project. We printed musical scores that had been developed by AI and built from sketches of Beethoven’s 10th. A pianist performed in a small concert hall in the museum in front of a group of journalists, musicologists and Beethoven experts.

We challenged audiences to figure out where Beethoven’s sentences end and where the AI ​​extrapolation begins. They could not.

A few days later, one of those AI-generated scores was performed by a string quartet at a press conference. Only those who were intimately familiar with Beethoven’s sketches for the 10th Symphony could determine when the AI-generated parts arrived.

The success of these tests told us that we were on the right track. But it was only a few minutes of music. There was still a lot of work to be done.

Ready for the world

At every moment, the genius of Beethoven presented itself, challenging us to do better. As the project evolved, so did the AI. Over the next 18 months, we built and orchestrated two entire movements of over 20 minutes each.

We anticipate some setback from this work – those who will say that the arts should be off limits to AI, and that AI does not have to try to replicate the human creative process. Yet when it comes to the arts, I see AI not as a replacement, but as a tool, a tool that opens doors for artists to express themselves in new ways.

This project would not have been possible without the expertise of human historians and musicians. It took an immense amount of work and, yes, creative thinking to achieve this goal.

At one point, one of the team’s music experts said the AI ​​reminded him of a passionate music student who practices every day, learns, and gets better and better.

Now this student, having taken over from Beethoven, is ready to present the 10th Symphony to the world.

Ahmed Elgammal, professor, director of the Art & AI Lab, Rutgers University

This article is republished from The Conversation under a Creative Commons license. Read the original article.


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