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

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

URI
https://arbor.bfh.ch/handle/arbor/43866
Version
Published
Date Issued
2021
Author(s)
Wey, Yannick  
Metzig, Cornelia
Type
Article
Language
English
Subjects

Classification folk m...

Abstract
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.
Subjects
M Music
DOI
10.24451/arbor.20511
https://doi.org/10.24451/arbor.20511
Publisher DOI
10.1177/20592043211004497
Journal or Serie
Music & Science
ISSN
2059-2043
Publisher URL
https://journals.sagepub.com/doi/10.1177/20592043211004497
Organization
Hochschule der Künste Bern  
Institut Interpretation  
Volume
4
Submitter
Wey, Yannick
Citation apa
Wey, Y., & Metzig, C. (2021). Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes. In Music & Science (Vol. 4). https://doi.org/10.24451/arbor.20511
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