Tonal Mode Detection Based on the Triple Composite Signature of Fifths

In this article, a novel algorithm for tonal mode classification utilizing the signature of fifths is presented. The proposed method is an extension of previously developed algorithms used for determining the key and key signature within the Western tonal system. The core idea of the algorithm is to analyze the entire piece as well as its most important excerpts, namely, the beginning and the end. The analysis of these three samples (beginning, end, and entire piece) involves the calculation of their corresponding signatures of fifths, which constitute two-dimensional sets of vectors inscribed in the circle of fifths. The length of each vector comprising the signature of fifths corresponds to the multiplicity of notes associated with a particular pitch class, while its direction is related to the position of that pitch class with respect to the circle of fifths. Based on the obtained signatures of fifths, the so-called Triple Composite Signature of Fifths is created, for which both the main directed axis and the major/minor mode axis are determined. Tonal mode is then established heuristically, based on the values of angles between the characteristic vectors of each sample’s signature of fifths and the major/minor mode axis of the Triple Composite Signature of Fifths. The process of tonal mode classification involves defining a tonal mode indicator, which assumes the values of 1 for major and −1 for minor tonality. To evaluate the effectiveness of the developed algorithm, a series of experiments was carried out using datasets of works from the Romantic period by F. Chopin and F. Schubert, as well as piano compositions from various eras. The results confirmed the high effectiveness of the proposed method in identifying tonal mode.

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Publication Details

Journal
Applied Sciences
Published
2026-01-30
DOI
https://doi.org/10.3390/app16031409
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
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article

Tonal Mode Detection Based on the Triple Composite Signature of Fifths

Tomasz Łukaszewicz, Zuzanna Kania, Dariusz Kania
Applied Sciences
Music and Audio Processing
article

Tonal Mode Detection Based on the Triple Composite Signature of Fifths

Tomasz Łukaszewicz, Zuzanna Kania, Dariusz Kania
article en

Abstract

In this article, a novel algorithm for tonal mode classification utilizing the signature of fifths is presented. The proposed method is an extension of previously developed algorithms used for determining the key and key signature within the Western tonal system. The core idea of the algorithm is to analyze the entire piece as well as its most important excerpts, namely, the beginning and the end. The analysis of these three samples (beginning, end, and entire piece) involves the calculation of their corresponding signatures of fifths, which constitute two-dimensional sets of vectors inscribed in the circle of fifths. The length of each vector comprising the signature of fifths corresponds to the multiplicity of notes associated with a particular pitch class, while its direction is related to the position of that pitch class with respect to the circle of fifths. Based on the obtained signatures of fifths, the so-called Triple Composite Signature of Fifths is created, for which both the main directed axis and the major/minor mode axis are determined. Tonal mode is then established heuristically, based on the values of angles between the characteristic vectors of each sample’s signature of fifths and the major/minor mode axis of the Triple Composite Signature of Fifths. The process of tonal mode classification involves defining a tonal mode indicator, which assumes the values of 1 for major and −1 for minor tonality. To evaluate the effectiveness of the developed algorithm, a series of experiments was carried out using datasets of works from the Romantic period by F. Chopin and F. Schubert, as well as piano compositions from various eras. The results confirmed the high effectiveness of the proposed method in identifying tonal mode.

Applied SciencesVol. 16(3)
Silesian University of Technology (PL), University of Economics in Katowice (PL), University of Occupational Safety Management in Katowice (PL)
Openalex Percentile: Top 72%
Music and Audio Processing
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