Dynamic cluster structure and predictive modelling of music creation style distributions
Rajsuryan Singh, Eita Nakamura

TL;DR
This study models and predicts the evolution of music creation styles across cultures using statistical and evolutionary models, revealing consistent intra- and inter-cluster dynamics in musical style distributions.
Contribution
It introduces a fitness-based evolutionary model that captures intra- and inter-cluster dynamics in music styles, improving prediction accuracy of style distribution changes.
Findings
Intra-cluster dynamics like contraction and shift are significant across cultures.
The evolutionary model effectively predicts future music style distributions.
Intra-cluster dynamics are crucial in understanding cultural evolution of music.
Abstract
We investigate the dynamics of music creation style distributions to understand cultural evolution involving advanced intelligence. Using statistical modelling methods and several musical statistics extracted from datasets of popular music created in Japan and the United States (the US), we explored the dynamics of cluster structures and constructed a fitness-based evolutionary model to analyze and predict the evolution of music creation style distributions. We found that intra-cluster dynamics, such as the contraction of a cluster and the shift of a cluster centre, as well as inter-cluster dynamics represented by clusters' relative frequencies, often exhibit notable dynamical modes that hold across the cultures and different musical aspects. Additionally, we found that the evolutionary model incorporating these dynamical modes is effective for predicting the future creation style…
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Taxonomy
TopicsMusic and Audio Processing · Animal Vocal Communication and Behavior · Music Technology and Sound Studies
