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What if the 'When' Implies the 'What'?: Human harmonic analysis datasets clarify the relative role of the separate steps in automatic tonal analysis.

Gotham, Mark; Kleinertz, Rainer; Weiß, Christof; Müller, Meinard; Klauk, Stephanie

Authors

Rainer Kleinertz

Christof Weiß

Meinard Müller

Stephanie Klauk



Contributors

Jin Ha Lee
Editor

Alexander Lerch
Editor

Zhiyao Duan
Editor

Juhan Nam
Editor

Preeti Rao
Editor

Peter van Kranenburg
Editor

Ajay Srinivasamurthy
Editor

Abstract

This paper uses the emerging provision of human harmonic analyses to assess how reliably we can map from knowing only when chords and keys change to a full identification of what those chords and keys are. We do this with a simple implementation of pitch class profile matching methods, partly to provide a benchmark score against which to judge the performance of less readily interpretable machine learning systems, many of which explicitly separate these when and what tasks and provide performance evaluation for these separate stages. Additionally, as this 'oracle'-style, 'perfect' segmentation information will not usually be available in practice, we test the sensitivity of these methods to slight modifications in the position of segment boundaries by introducing deliberate errors. This study examines several corpora. The focus on is symbolic data, though we include one audio dataset for comparison. The code and corpora (of symbolic scores and analyses) are available within: https://github.com/MarkGotham/When-in-Rome

Citation

Gotham, M., Kleinertz, R., Weiß, C., Müller, M., & Klauk, S. (2021). What if the 'When' Implies the 'What'?: Human harmonic analysis datasets clarify the relative role of the separate steps in automatic tonal analysis. In J. H. Lee, A. Lerch, Z. Duan, J. Nam, P. Rao, P. V. Kranenburg, & A. Srinivasamurthy (Eds.), Proceedings of the 22nd International Society for Music Information Retrieval Conference (229-236)

Conference Name ISMIR 2021: 22nd International Society for Music Information Retrieval Conference
Conference Location Online
Start Date Nov 7, 2021
End Date Nov 12, 2021
Acceptance Date Jun 1, 2021
Online Publication Date Nov 7, 2021
Publication Date 2021
Deposit Date Feb 29, 2024
Pages 229-236
Series Title Proceedings of the 22nd International Conference on Music Information Retrieval, ISMIR 2021
Book Title Proceedings of the 22nd International Society for Music Information Retrieval Conference
ISBN 9781732729902
Public URL https://durham-repository.worktribe.com/output/2273222
Publisher URL https://www.ismir.net/conferences/ismir2021.html