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Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes
by
Metzig, Cornelia
, Wey, Yannick
in
Classification
/ Melody
/ Regions
/ Yodeling
2021
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Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes
by
Metzig, Cornelia
, Wey, Yannick
in
Classification
/ Melody
/ Regions
/ Yodeling
2021
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Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes
Journal Article
Machine Learning Classification of Regional Swiss Yodel Styles Based on Their Melodic Attributes
2021
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Overview
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.
Publisher
SAGE Publications,Sage Publications Ltd,SAGE Publishing
Subject
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