Craig Vear
Building an Embodied Musicking Dataset for co-creative music-making
Vear, Craig; Poltronieri, Fabrizio; Di Donato, Balandino; Zhang, Yawen; Benerradi, Johann; Hutchinson, Simon; Turowski, Paul; Shell, Jethro; Malekmohamadi, Hossein
Authors
Fabrizio Poltronieri
Dr Balandino Di Donato B.DiDonato@napier.ac.uk
Lecturer
Yawen Zhang
Johann Benerradi
Simon Hutchinson
Paul Turowski
Jethro Shell
Hossein Malekmohamadi
Abstract
In this paper, we present our findings of the design, development and deployment of a proof-of-concept dataset that captures some of the physiological, musicological, and psychological aspects of embodied musicking. After outlining the conceptual elements of this research, we explain the design of the dataset and the process of capturing the data. We then introduce two tests we used to evaluate the dataset: a) using data science techniques and b) a practice-based application in an AI-robot digital score. The results from these tests are conflicting: from a data science perspective the dataset could be considered garbage, but when applied to a real-world musicking situation performers reported it was transformative and felt to be ‘co-creative’. We discuss this duality and pose some important questions for future study. However, we feel that the datatset contains a set of relationships that are useful to explore in the creation of music.
Citation
Vear, C., Poltronieri, F., Di Donato, B., Zhang, Y., Benerradi, J., Hutchinson, S., Turowski, P., Shell, J., & Malekmohamadi, H. (2024, April). Building an Embodied Musicking Dataset for co-creative music-making. Presented at Evostar 2024: The Leading European Event on Bio‑Inspired Computation, Aberystwyth, Wales, United Kingdom
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | Evostar 2024: The Leading European Event on Bio‑Inspired Computation |
Start Date | Apr 3, 2024 |
End Date | Apr 5, 2024 |
Online Publication Date | Mar 29, 2024 |
Publication Date | 2024 |
Deposit Date | May 23, 2024 |
Publicly Available Date | Mar 30, 2025 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 14633 |
Pages | 373-388 |
Series Title | Lecture Notes in Computer Science |
Series Number | 14633 |
Series ISSN | 0302-9743 |
Book Title | Evostar 2024 |
ISBN | 978-3-031-56991-3 |
DOI | https://doi.org/10.1007/978-3-031-56992-0_24 |
Keywords | dataset, music performance, embodied AI |
Publisher URL | https://www.springer.com/gp/computer-science/lncs |
Files
This file is under embargo until Mar 30, 2025 due to copyright reasons.
Contact repository@napier.ac.uk to request a copy for personal use.
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