Machine learning-based modelling of expressive style influences among famous cello interpreters

Ovelar Anderson, Sebastian Roberto

Machine learning-based modelling of expressive style influences among famous cello interpreters

Citació

Ovelar Anderson, S. Machine learning-based modelling of expressive style influences among famous cello interpreters. 2021. handle: http://hdl.handle.net/10230/48869

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Resum

The study of the subtle changes musicians introduce when playing a piece has been an area of interest in the past decades. As new and more powerful machines are available, we can build models that imitate these changes. In this project, we have trained models using machine learning methods to predict the expressive performance in terms of timing and dynamics that famous Cellists introduce. Models for timing and dynamics were trained using recordings of famous cello players performing a piece that was segmented into notes. The resulting models were compared to identify expressive performance resemblances among the cello artists by predicting a player’s performance using the expressive performance models of the other ones.