Information content of note transitions in the music of J. S. Bach
Suman Kulkarni, Sophia U. David, Christopher W. Lynn, Dani S. Bassett

TL;DR
This paper introduces a network-based framework to quantify and analyze the information content of J. S. Bach's music, revealing how different compositions encode and communicate information efficiently through their structure.
Contribution
The study develops a novel network science and information theory framework to quantify musical information and applies it to Bach's compositions, uncovering structural patterns related to information communication.
Findings
Different composition types cluster by information content.
Music networks encode large amounts of information efficiently.
High heterogeneity and clustering enable rapid information communication.
Abstract
Music has a complex structure that expresses emotion and conveys information. Humans process that information through imperfect cognitive instruments that produce a gestalt, smeared version of reality. How can we quantify the information contained in a piece of music? Further, what is the information inferred by a human, and how does that relate to (and differ from) the true structure of a piece? To tackle these questions quantitatively, we present a framework to study the information conveyed in a musical piece by constructing and analyzing networks formed by notes (nodes) and their transitions (edges). Using this framework, we analyze music composed by J. S. Bach through the lens of network science and information theory. Regarded as one of the greatest composers in the Western music tradition, Bach's work is highly mathematically structured and spans a wide range of compositional…
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Taxonomy
TopicsMusic and Audio Processing · Neuroscience and Music Perception · Music Technology and Sound Studies
