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A computational study on outliers in world music
Maria Panteli1, Emmanouil Benetos1, Simon Dixon1
1Centre for Digital Music, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom.
Plos One
|December 19, 2017
Summary
This study identified unique world music outliers using computational analysis of 8200 folk recordings. Botswana
Area of Science:
- Ethnomusicology
- Music Information Retrieval
- Computational Musicology
Background:
- Comparative analysis of world music cultures is a long-standing ethnomusicological pursuit.
- Advances in Music Information Retrieval and sound archives enable large-scale computational analysis of global music.
Purpose of the Study:
- To investigate music similarity in a large corpus of world folk and traditional music.
- To identify distinct musical recordings, termed 'outliers', within the corpus.
- To analyze musical attributes and styles contributing to national music uniqueness.
Main Methods:
- Utilized signal processing to extract audio features from 8200 recordings across 137 countries.
- Employed data mining techniques for quantifying music similarity and detecting outliers.
- Applied spatial statistics to incorporate geographical correlations in the analysis.
Main Results:
- Identified Botswana as the country with the most distinct music recordings overall.
- Determined China as the country with the most distinct recordings when considering spatial correlation.
- Detailed comparison of musical attributes and styles defining national music uniqueness.
Conclusions:
- Computational methods provide powerful tools for large-scale ethnomusicological research.
- Botswana and China exhibit unique musical characteristics within the studied corpus.
- Understanding music distinctiveness enhances global music cultural appreciation.
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