Computationally creative systems for music have recently achieved impressive results, fuelled by progress in generative machine learning. However, black-box approaches have raised fundamental concerns for ethics, accountability, explainability, and musical plausibility. To enable trustworthy machine creativity, we introduce the Harmonic Memory, a Knowledge Graph (KG) of harmonic patterns extracted from a large and heterogeneous musical corpus. By leveraging a cognitive model of tonal harmony, chord progressions are segmented into meaningful structures, and patterns emerge from their comparison via harmonic similarity. Akin to a music memory, the KG holds temporal connections between consecutive patterns, as well as salient similarity relationships. After demonstrating the validity of our choices, we provide examples of how this design enables novel pathways for combinational creativity. The memory provides a fully accountable and explainable framework to inspire and support creative professionals – allowing for the discovery of progressions consistent with given criteria, the recomposition of harmonic sections, but also the co-creation of new progressions.

De Berardinis J., Meroño-Peñuela A., Poltronieri A., Presutti V. (2023). The Harmonic Memory: a Knowledge Graph of harmonic patterns as a trustworthy framework for computational creativity. New York, NY : Association for Computing Machinery [10.1145/3543507.3587428].

The Harmonic Memory: a Knowledge Graph of harmonic patterns as a trustworthy framework for computational creativity

Poltronieri A.
Co-primo
Software
;
Presutti V.
Co-primo
Supervision
2023

Abstract

Computationally creative systems for music have recently achieved impressive results, fuelled by progress in generative machine learning. However, black-box approaches have raised fundamental concerns for ethics, accountability, explainability, and musical plausibility. To enable trustworthy machine creativity, we introduce the Harmonic Memory, a Knowledge Graph (KG) of harmonic patterns extracted from a large and heterogeneous musical corpus. By leveraging a cognitive model of tonal harmony, chord progressions are segmented into meaningful structures, and patterns emerge from their comparison via harmonic similarity. Akin to a music memory, the KG holds temporal connections between consecutive patterns, as well as salient similarity relationships. After demonstrating the validity of our choices, we provide examples of how this design enables novel pathways for combinational creativity. The memory provides a fully accountable and explainable framework to inspire and support creative professionals – allowing for the discovery of progressions consistent with given criteria, the recomposition of harmonic sections, but also the co-creation of new progressions.
2023
Proceedings of the ACM Web Conference 2023 (WWW '23)
3873
3882
De Berardinis J., Meroño-Peñuela A., Poltronieri A., Presutti V. (2023). The Harmonic Memory: a Knowledge Graph of harmonic patterns as a trustworthy framework for computational creativity. New York, NY : Association for Computing Machinery [10.1145/3543507.3587428].
De Berardinis J.; Meroño-Peñuela A.; Poltronieri A.; Presutti V.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/932133
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