Penulis: Edi Noersasongko, Pulung Nurtantio Andono, Guruh Fajar Sidik, Arry Maulana Syarif
SYNOPSIS
Computational Gamelan Music: Rule-Based Music Generation for Camelan presents a systematic approach to computational gamelan music generation using symbolic representation, musical knowledge, rules, constraints, and weighted selection. The book introduces the musical structures required for computational processing and explains how gamclan compositions can be transfonned into symbolic representations. These representations are subsequently used to construct a Musical Knowledge Base containing pitch distributions, gatra patterns, seleh distributions, inter- gatra transitions, melodic movements, and other musical characteristics.
Building on this knowledge, the book develops a rule-based generation process that transforms music patterns and relationship into compositional decisions. Rules and com;tralnts provide control over structural and musical characteristics, while weighted selection allows frequently occurring patterns in the source data to have greater influence during generation. The resulting compositions are then evaluated using structural and distributional measures. The evaluation examines five dimensions: Pitch Distribution, Gatra Pattern Distribution, Seleh Distribution, Inter-Gatra Transition Distribution, and Melodic Movement Distribution. A source-to-source baseline is used to provide a reference for interpreting the similarity between generated and source compositions.
The book also presents parsing and text-based export of generated symbolic music, followed by a discussion of the limitations and future directions of rule-based generation. These include challenges in representation, data, musical knowledge acquisition, rule complexity, evaluation, scalability, and generalization, as well as opportunities for learning-based, adaptive, interactive, and human-in-the-loop approaches. Designed for students, researchers, and developers, this book provides both conceptual foundations and practical guidance for computational gamelan music generation.