KNOWLEDGE-DRIVEN HARMONIZATION MODEL FOR TONAL MUSIC

Mariusz Rybnik; Władysław Homenda

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Paper

KNOWLEDGE-DRIVEN HARMONIZATION MODEL FOR TONAL MUSIC

In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, 445-450, 2012 , Vilamoura, Algarve, Portugal

Authors: Mariusz Rybnik ¹ and Władysław Homenda ²

Affiliations: ¹ University of Bialystok, Poland ; ² University of Bialystok and Warsaw University of Technology, Poland

Keyword(s): Musical work, Harmony, Harmonization, Tonality, Knowledge-based systems.

Abstract: The paper proposes an approach to an automatic harmonization of musical work, and is based on the knowledge of music theory. It may be described as knowledge-based, being in contrast to a data-driven approach, that extracts relationships from examples. Our approach emphasizes universality, understood as the possibility of direct model modifications in order to obtain varied harmony characteristics (as for example a complicated and unusual harmony, or a simple harmony using only a small subset of harmonic functions and few modifiers). Therefore it is configurable by changing the internal parameters of harmonization mechanisms (among others: harmonic functions excitements with note pitches, note importance regarding among others horizontal position in measure and vertical position in voices structure, successions of neighboring harmonic functions), as well as importance weights attached to each of these mechanisms.

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Paper citation in several formats:

Rybnik, M. and Homenda, W. (2012). KNOWLEDGE-DRIVEN HARMONIZATION MODEL FOR TONAL MUSIC. In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-8425-95-9; ISSN 2184-433X, SciTePress, pages 445-450. DOI: 10.5220/0003889604450450

@conference{icaart12,
author={Mariusz Rybnik. and Władysław Homenda.},
title={KNOWLEDGE-DRIVEN HARMONIZATION MODEL FOR TONAL MUSIC},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2012},
pages={445-450},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003889604450450},
isbn={978-989-8425-95-9},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - KNOWLEDGE-DRIVEN HARMONIZATION MODEL FOR TONAL MUSIC
SN - 978-989-8425-95-9
IS - 2184-433X
AU - Rybnik, M.
AU - Homenda, W.
PY - 2012
SP - 445
EP - 450
DO - 10.5220/0003889604450450
PB - SciTePress