Digitally deconstructing Beethoven

Beethoven’s music was dominated by just a few major chords, researchers suggest.

That’s not a criticism; it’s their take on an in-depth statistical analysis of the great composer’s work made possible by digital technology.

Martin Rohrmeier and colleagues, from Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, looked in detail at all 16 string quartets Beethoven wrote in the first quarter of the nineteenth century – the last completed in 1826, just before his death.

That’s more than eight hours of music in all, comprising around 30,000 chord annotations.

The aim was to create a digital resource that would allow the researchers to look for patterns that underpinned Beethoven’s compositional style and creative choices: his “statistical signature”.

Anyone who has dabbled in music knows about the dominant and tonic chords, which have central roles in creating tension and establishing musical phrases. There are, however, many types of chords, including numerous variants of the dominant and tonic. 

The Beethoven string quartets contain more than 1000 different types, the researchers say. However, their study finds that very few chords govern most of the music. 

As expected from theory on music from the classical period, it shows that the compositions are particularly dominated by the dominant and tonic chords and their many variants. Also, the most frequent transition from one chord to the next happens from the dominant to the tonic. 

Chords strongly select for their order and, thus, define the direction of musical time. The statistical methodology also characterises Beethoven’s specific composition style for the string quartets, through a distribution of all the chords he used, how often they occur, and how they commonly transition from one to the other.

“New state-of-the-art methods in statistics and data science make it possible for us to analyse music in ways that were out of reach for traditional musicology,” says Rohrmeier, who leads EPFL’s Digital and Cognitive Musicology Lab. 

“The young field of digital musicology is currently advancing a whole new range of methods and perspectives. The aim of our lab is to understand how music works.”

They will now turn their attention to other composers, and invite other researchers to “join our search for the statistical basis of the inner workings of music”.

The findings are published in the journal PLOS ONE.

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