Statistical Methods in Music Corpus Studies: Application, UseCases, and Best Practice Examples. Müllensiefen, D. & Frieler, K. In Shanahan, D., Burgoyne, J. A., & Quinn, I., editors, The Oxford Handbook of Music and Corpus Studies. Oxford University Press, 1 edition, February, 2022. ![Statistical Methods in Music Corpus Studies: Application, UseCases, and Best Practice Examples [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex In this chapter, the authors explain that there are two common goals in musical corpus analysis. The rst is the description and comparison of musical corpora, the second is to establish relationships between musical structures and extra-musical data, which can refer to metadata of a particular musical piece (genre, style, and period labels, composer and performer attributions, etc.) or to listeners' perceptions and evaluations. The authors give a brief overview of basic and advanced statistical methods that have been employed in music corpus studies. The chapter covers descriptive statistics and visualizations, feature selection and aggregation using principal component analysis. In addition, random forests and linear regression methods for use in the context of corpus studies are brie y explained, as well as supervised and unsupervised classi cation techniques. Each topic and method is introduced with a conceptual explanation, suggestions for its application, and usage scenarios from the research literature.
@InCollection{ mullensiefen.ea2022-statistical,
author = {M\"{u}llensiefen, Daniel and Frieler, Klaus},
year = {2022},
title = {Statistical {Methods} in {Music} {Corpus} {Studies}:
{Application}, {UseCases}, and {Best} {Practice}
{Examples}},
edition = {1},
isbn = {978-0-19-094544-2 978-0-19-094547-3},
url = {https://academic.oup.com/edited-volume/41992},
abstract = {In this chapter, the authors explain that there are two
common goals in musical corpus analysis. The rst is the
description and comparison of musical corpora, the second
is to establish relationships between musical structures
and extra-musical data, which can refer to metadata of a
particular musical piece (genre, style, and period labels,
composer and performer attributions, etc.) or to
listeners' perceptions and evaluations. The authors give a
brief overview of basic and advanced statistical methods
that have been employed in music corpus studies. The
chapter covers descriptive statistics and visualizations,
feature selection and aggregation using principal
component analysis. In addition, random forests and linear
regression methods for use in the context of corpus
studies are brie y explained, as well as supervised and
unsupervised classi cation techniques. Each topic and
method is introduced with a conceptual explanation,
suggestions for its application, and usage scenarios from
the research literature.},
language = {en},
urldate = {2022-12-22},
booktitle = {The {Oxford} {Handbook} of {Music} and {Corpus}
{Studies}},
publisher = {Oxford University Press},
editor = {Shanahan, Daniel and Burgoyne, John Ashley and Quinn,
Ian},
month = feb,
doi = {10.1093/oxfordhb/9780190945442.001.0001}
}
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