Limitations from Assumptions in Generative Music Evaluation

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@Article{Loughran:2017:JCMS,
  author =       "Roisin Loughran and Michael O'Neill",
  title =        "Limitations from Assumptions in Generative Music
                 Evaluation",
  journal =      "Journal of Creative Music Systems",
  year =         "2017",
  volume =       "2",
  number =       "1",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, Autonomous
                 systems, creativity, evaluation, music generation",
  ISSN =         "2399-7656",
  URL =          "http://jcms.org.uk/issues/Vol2Issue1/limitations-from-assumptions/article.html",
  URL =          "http://jcms.org.uk/issues/Vol2Issue1/limitations-from-assumptions/Limitations%20from%20Assumptions%20in%20Generative%20Music%20Evaluation.pdf",
  size =         "31 pages",
  abstract =     "The merit of a given piece of music is difficult to
                 evaluate objectively; the merit of a computational
                 system that creates such a piece of music may be even
                 more so. In this article, we propose that there may be
                 limitations resulting from assumptions made in the
                 evaluation of autonomous compositional or creative
                 systems. The article offers a review of computational
                 creativity, evolutionary compositional methods and
                 current methods of evaluating creativity. We propose
                 that there are potential limitations in the discussion
                 and evaluation of generative systems from two
                 standpoints. First, many systems only consider
                 evaluating the final artefact produced by the system
                 whereas computational creativity is defined as a
                 behaviour exhibited by a system. Second, artefacts tend
                 to be evaluated according to recognised human
                 standards. We propose that while this may be a natural
                 assumption, this focus on human-like or human-based
                 preferences could be limiting the potential and
                 generality of future music generating or creative-AI
                 systems",
}

Genetic Programming entries for Roisin Loughran Michael O'Neill

Citations