Data-based melody generation through multi-objective evolutionary computation. Issue 2 (3rd May 2016)

• Record Type: Journal Article
• Authors: Ponce de León, Pedro J.; Iñesta, José M.; Calvo-Zaragoza, Jorge; Rizo, David
• Is Part Of: Journal of mathematics and music. Volume 10:Issue 2(2016)
• Page Start: 173
• Page End: 192
• Publication Date: 2016-05-03
• Subjects: machine learning -- evolutionary algorithms -- composition -- melody -- tree representation -- multi-objective optimization; 68T05; applied computing -- sound and music computing -- computing methodologies -- learning from critiques -- computing methodologies -- genetic programming; Music theory -- Periodicals; Music -- Mathematical models -- Periodicals; Music -- Mathematics -- Periodicals; 781.2
• DOI: 10.1080/17459737.2016.1188171
• Languages: English
• ISSNs: 1745-9737

Abstract

Abstract : Genetic-based composition algorithms are able to explore an immense space of possibilities, but the main difficulty has always been the implementation of the selection process. In this work, sets of melodies are utilized for training a machine learning approach to compute fitness, based on different metrics. The fitness of a candidate is provided by combining the metrics, but their values can range through different orders of magnitude and evolve in different ways, which makes it hard to combine these criteria. In order to solve this problem, a multi-objective fitness approach is proposed, in which the best individuals are those in the Pareto front of the multi-dimensional fitness space. Melodic trees are also proposed as a data structure for chromosomic representation of melodies and genetic operators are adapted to them. Some experiments have been carried out using a graphical interface prototype that allows one to explore the creative capabilities of the proposed system. An Online Supplement is provided and can be accessed athttp://dx.doi.org/10.1080/17459737.2016.1188171, where the reader can find some technical details, information about the data used, generated melodies, and additional information about the developed prototype and its performance.