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-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 204-211Publication milestones
- Published - 06/2015
Publication status
Published - 06/2015
Publisher
Utah State University PressISBN (Print)
978-0-8425-2970-9Publication IDs
- Scopus: 85061165858
Host publication title
Proceedings of the Sixth International Conference on Computational Creativity June 2015Abstract
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.
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Citations
26
Captures
28
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Final published version
