COMPARING HUMAN AND COMPUTATIONAL MODELS OF MUSIC PREDICTION

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dc.contributor.authorWitten, Ian H.eng
dc.contributor.authorManzara, Leonard C.eng
dc.contributor.authorConklin, Darrelleng
dc.date.accessioned2008-02-27T22:30:12Z
dc.date.available2008-02-27T22:30:12Z
dc.date.computerscience1999-05-27eng
dc.date.issued1992-05-01eng
dc.description.abstractThe information content of each successive note in a piece of music is not an intrinsic musical property but depends on the listener's own model of a genre of music. Human listeners' models can be elicited by having them guess successive notes and assign probabilities to their guesses by gambling. Computational models can be constructed by developing a structural framework for prediction, and "training" the system by having it assimilate a corpus of sample compositions and adjust its internal probability estimates accordingly. These two modeling techniques turn out to yield remarkably similar values for the information content, or "entropy," of the Bach chorale melodies. While previous research has concentrated on the overall information content of whole pieces of music, the present study evaluates and compares the two kinds of model in fine detail. Their predictions for two particular chorale melodies are analyzed on a note-by-note basis, and the smoothed information profiles of the chorales are examined and compared. Apart from the intrinsic interest of comparing human with computational models of music, several conclusions are drawn for the improvement of computational models.eng
dc.description.notesWe are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.caeng
dc.identifier.department1992-477-15eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/31144
dc.identifier.urihttp://hdl.handle.net/1880/46196
dc.language.isoEngeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectComputer Scienceeng
dc.titleCOMPARING HUMAN AND COMPUTATIONAL MODELS OF MUSIC PREDICTIONeng
dc.typeunknown
thesis.degree.disciplineComputer Scienceeng
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