Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes

Wey, Yannick; Metzig, Cornelia (2021). Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes Music & Science, 4, p. 205920432110044. 10.1177/20592043211004497

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A classification of wordless yodel melodies from five different regions in Switzerland was made. For our analysis, we used a total of 217 yodel tunes from five regions, which can be grouped into two larger regions, central and north-eastern Switzerland. The results show high accuracy of classification, therefore confirming the existence of regional differences in yodel melodies. The most salient features, such as rhythmic patterns or intervals, demonstrate some of the key differences in pairwise comparisons, which can be confirmed by a postanalysis survey of the relevant scores.

Item Type:	Journal Article (Original Article)
Division/Institute:	Bern Academy of the Arts Bern Academy of the Arts > Institute Interpretation
Name:	Wey, Yannick0000-0002-2416-1285 and Metzig, Cornelia
Subjects:	M Music and Books on Music > M Music
ISSN:	2059-2043
Language:	English
Submitter:	Yannick Wey
Date Deposited:	16 May 2024 10:45
Last Modified:	19 May 2024 01:39
Publisher DOI:	10.1177/20592043211004497
Uncontrolled Keywords:	Classification folk music machine learning Switzerland yodel
ARBOR DOI:	10.24451/arbor.20511
URI:	https://arbor.bfh.ch/id/eprint/20511