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SMUG: Scientific Music Generator

  • Marco Scirea
    ,
  • Gabriella A B Barros
    ,
  • Julian Togelius
    ,
  • Noor Shaker
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 204-211

Publication milestones

  • Published - 06/2015

Publication status

Published - 06/2015

Publisher

Utah State University Press
978-0-8425-2970-9

Publication IDs

  • Scopus: 85061165858

Host publication title

Proceedings of the Sixth International Conference on Computational Creativity June 2015

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.

Publication metrics

PlumX

Citations
26
Captures
28