The Annotated Mozart Sonatas: Score, Harmony, and Cadence. Hentschel, J., Neuwirth, M., & Rohrmeier, M. Transactions of the International Society for Music Information Retrieval, 4(1):67–80, may, 2021. ![The Annotated Mozart Sonatas: Score, Harmony, and Cadence [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 1 download This article describes a new expert-labelled dataset featuring harmonic, phrase, and cadence analyses of all piano sonatas by W.A. Mozart. The dataset draws on the DCML standard for harmonic annotation and is being published adopting the FAIR principles of Open Science. The annotations have been verified using a data triangulation procedure which is presented as an alternative approach to handling annotator subjectivity. This procedure is suited for ensuring consistency, within the dataset and beyond, despite the high level of analytical detail afforded by the employed harmonic annotation syntax. The harmony labels also encode contextual information and are therefore suited for investigating music theoretical questions related to tonal harmony and the harmonic makeup of cadences in the classical style. Apart from providing basic statistical analyses characterizing the dataset, its music theoretical potential is illustrated by two preliminary experiments, one on the terminal harmonies of cadences and the other on the relation between performance durations and harmonic density. Furthermore, particular features can be selected to produce more coarse-grained training data, for example for chord detection algorithms that require less analytical detail. Facilitating the dataset's reusability, it comes with a Python script that allows researchers to easily access various representations of the data tailored to their particular needs.
@Article{ hentschel.ea2021-annotated,
author = {Hentschel, Johannes and Neuwirth, Markus and Rohrmeier,
Martin},
year = {2021},
title = {The Annotated Mozart Sonatas: Score, Harmony, and
Cadence},
abstract = {This article describes a new expert-labelled dataset
featuring harmonic, phrase, and cadence analyses of all
piano sonatas by W.A. Mozart. The dataset draws on the
DCML standard for harmonic annotation and is being
published adopting the FAIR principles of Open Science.
The annotations have been verified using a data
triangulation procedure which is presented as an
alternative approach to handling annotator subjectivity.
This procedure is suited for ensuring consistency, within
the dataset and beyond, despite the high level of
analytical detail afforded by the employed harmonic
annotation syntax. The harmony labels also encode
contextual information and are therefore suited for
investigating music theoretical questions related to tonal
harmony and the harmonic makeup of cadences in the
classical style. Apart from providing basic statistical
analyses characterizing the dataset, its music theoretical
potential is illustrated by two preliminary experiments,
one on the terminal harmonies of cadences and the other on
the relation between performance durations and harmonic
density. Furthermore, particular features can be selected
to produce more coarse-grained training data, for example
for chord detection algorithms that require less
analytical detail. Facilitating the dataset's reusability,
it comes with a Python script that allows researchers to
easily access various representations of the data tailored
to their particular needs.},
doi = {10.5334/tismir.63},
issn = {2514-3298},
journal = {Transactions of the International Society for Music
Information Retrieval},
keywords = {cadence,classical style,computational
musicology,expert-annotated dataset,piano music,tonal
harmony},
mendeley-tags= {computational musicology},
month = {may},
number = {1},
pages = {67--80},
url = {http://transactions.ismir.net/articles/10.5334/tismir.63/},
volume = {4}
}
Downloads: 1
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The dataset draws on the\n DCML standard for harmonic annotation and is being\n published adopting the FAIR principles of Open Science.\n The annotations have been verified using a data\n triangulation procedure which is presented as an\n alternative approach to handling annotator subjectivity.\n This procedure is suited for ensuring consistency, within\n the dataset and beyond, despite the high level of\n analytical detail afforded by the employed harmonic\n annotation syntax. The harmony labels also encode\n contextual information and are therefore suited for\n investigating music theoretical questions related to tonal\n harmony and the harmonic makeup of cadences in the\n classical style. Apart from providing basic statistical\n analyses characterizing the dataset, its music theoretical\n potential is illustrated by two preliminary experiments,\n one on the terminal harmonies of cadences and the other on\n the relation between performance durations and harmonic\n density. 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