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A Structural Theory of Rhythm Notation Based on Tree Representations and Term Rewriting Read chapter Read first chapter

2015 | OriginalPaper | Chapter

A Corpus-Sensitive Algorithm for Automated Tonal Analysis

Author : Christopher Wm. White

Published in: Mathematics and Computation in Music

Publisher: Springer International Publishing

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Abstract

A corpus-sensitive algorithm for tonal analysis is described. The algorithm learns a tonal vocabulary and syntax by grouping together chords that share scale degrees and occur in the same contexts and then compiling a transition matrix between these chord groups. When trained on a common-practice corpus, the resulting vocabulary of chord groups approximates traditional diatonic Roman numerals. These parameters are then used to determine the key and vocabulary items used in an unanalyzed piece of music. Such a corpus-based method highlights the properties of common-practice music on which traditional analysis is based, while offering the opportunity for analytical and pedagogical methods more sensitive to the characteristics of individual repertories.

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previous chapter Characteristics of Polyphonic Music Style and Markov Model of Pitch-Class Intervals
next chapter Finding Optimal Triadic Transformational Spaces with Dijkstra’s Shortest Path Algorithm
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Metadata
Title
A Corpus-Sensitive Algorithm for Automated Tonal Analysis
Author
Christopher Wm. White
Copyright Year
2015
Book
Mathematics and Computation in Music

Print ISBN: 978-3-319-20602-8

Electronic ISBN: 978-3-319-20603-5

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-20603-5_11

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