Data scientists in Switzerland have analyzed the patterns of Beethoven’s string quartets to look for patterns in the music
As the name suggests, a string quartet has four parts: Two violins, a viola and a cello. These four instruments play the different chords that make up the more than a thousand different chord types of the Beethoven String Quartets.
When the researchers of EFPL’s Digital and Cognitive Musicology Lab analysed the Beethoven quartets, they found that certain chords were more common than others, and that the progressions from one chord to the next also followed certain well-known patterns. This in itself is not a new discovery: it’s what music theorists already knew. But by picking up these well-known patterns, the researchers essentially showed that their data analysis method worked. From there, they took it a step further.
Musicologist and data scientist Fabian Moss is first author on this paper, as well as a pianist. He further explains his research in aOf course, this type of analysis is not limited to Beethoven. The same data science and statistical methods can be applied to other music collections, and form a starting point for further musicology analysis. As Moss, he would like to expand his research to other composers, and to include other dimensions of music beyond chord analysis.
Digital data analysis is not replacing traditional music theory, but it’s a new, science-driven branch of musicology that combines expertise of different fields. “The aim of our lab is to understand how music works,” head of the Digital and Cognitive Musicology Lab, Martin Rohrmeier. “New state-of-the-art methods in statistics and data science make it possible for us to analyze music in ways that were out of reach for traditional musicology.”I’m a freelance science writer, focused on stories behind the research. My writing about the intersection of science, art and culture has appeared in Nautilus, The Scien...
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