SMUG: Scientific Music Generator

Marco Scirea, Gabriella A B Barros, Julian Togelius, Noor Shaker

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Music is based on the real world. Composers use their day-to-day lives as inspiration to create rhythm and lyrics. Procedural music generators are capable of creating good quality pieces, and while some already use the world as inspiration, there is still much to be explored in this. We describe a system to generate lyrics and melodies from real-world data, in particular from academic papers. Through this we want to create a playful experience and establish a novel way of generating content (textual and musical) that could be applied to other domains, in particular to games. For melody generation, we present an approach to Markov chains evolution and briefly discuss the advantages and disadvantages of this approach.
Original languageEnglish
Title of host publicationProceedings of the Sixth International Conference on Computational Creativity June 2015
PublisherUtah State University Press
Publication dateJun 2015
Pages204-211
ISBN (Print)978-0-8425-2970-9
Publication statusPublished - Jun 2015

Keywords

  • music generation
  • lyrics generation
  • Markov chain

Fingerprint

Dive into the research topics of 'SMUG: Scientific Music Generator'. Together they form a unique fingerprint.

Cite this