Algorithmic Composition Using Narrative Structure and Tension
Algorithmic Composition Using Narrative Structure and Tension
Francisco Braga, Gilberto Bernardes, Roger B. Dannenberg, Nuno Correia
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
AI, Arts & Creativity. Pages 10045-10053.
https://doi.org/10.24963/ijcai.2025/1116
This paper describes an approach to algorithmic music composition that takes narrative structures as input, allowing composers to create music directly from narrative elements.
Creating narrative development in music remains a challenging task in algorithmic composition.
Our system addresses this by combining leitmotifs to represent characters, generative grammars for harmonic coherence, and evolutionary algorithms to align musical tension with narrative progression.
The system operates at different scales, from overall plot structure to individual motifs, enabling both autonomous composition and co-creation with varying degrees of user control.
Evaluation with compositions based on tales demonstrated the system's ability to compose music that supports narrative listening and aligns with its source narratives, while being perceived as familiar and enjoyable.
Keywords:
Application domains: Music and sound
Application domains: Other domains of art or creativity
Methods and resources: Evolutionary algorithms
Methods and resources: Other methods or resources
Theory and philosophy of arts and creativity in AI systems: Autonomous creative or artistic AI
Theory and philosophy of arts and creativity in AI systems: Computational paradigms, architectures and models for creativity
