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A Live Performance Rule System Informed by Irish Traditional Dance Music
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0009-0005-7428-4434
University of Nottingham, Nottingham, UK.ORCID iD: 0000-0001-8041-2520
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-2549-6367
University of Nottingham, Nottingham, UK.ORCID iD: 0000-0001-7879-7978
2026 (English)In: Music and Sound Generation in the AI Era - 16th International Symposium, CMMR 2023, Revised Selected Papers, Springer Nature , 2026, p. 127-139Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes ongoing work in programming a live performance system for interpreting melodies in ways that mimic Irish traditional dance music practice and that allows plug-and-play human interaction. Existing performance systems are almost exclusively aimed at piano performance and classical music and few are aimed specifically at traditional music. We develop a rule-based approach using expert knowledge that converts a melody into control parameters to synthesize an expressive MIDI performance, focusing on ornamentation, dynamics and subtle time deviation. Furthermore, we make the system controllable (e.g., via knobs or expression pedals) such that it can be controlled in real time by a musician. Our preliminary evaluations show the system can render expressive performances mimicking traditional practice and allows for engaging with Irish traditional dance music in new ways. We provide several examples online (See this website: https://www.kth.se/profile/bobs/page/research-data).

Place, publisher, year, edition, pages
Springer Nature , 2026. p. 127-139
Keywords [en]
Irish, music performance modeling, traditional music
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Computer Sciences Music Musicology
Identifiers
URN: urn:nbn:se:kth:diva-372795DOI: 10.1007/978-3-032-02042-0_9Scopus ID: 2-s2.0-105020024736OAI: oai:DiVA.org:kth-372795DiVA, id: diva2:2014590
Conference
16th International Symposium on Computer Music Multidisciplinary Research, CMMR 2023, Tokyo, Japan, November 13-17, 2023
Note

Not duplicate with diva 1795616 

Part of ISBN 9783032020413

QC 20251118

Available from: 2025-11-18 Created: 2025-11-18 Last updated: 2025-11-18Bibliographically approved

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Authority records

Amerotti, MarcoSturm, Bob L.T.

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