Evaluating a Chord-Labelling Algorithm

نویسندگان

  • Daniel Müllensiefen
  • David Lewis
  • Christophe Rhodes
  • Geraint A. Wiggins
چکیده

This paper outlines a method for evaluating a new chordlabelling algorithm using symbolic data as input. Excerpts from full-score transcriptions of 40 pop songs are used. The accuracy of the algorithm’s output is compared with that of chord labels from published song books, as assessed by experts in pop music theory. We are interested not only in the accuracy of the two sets of labels but also in the question of potential harmonic ambiguity as reflected the judges’ assessments. We focus, in this short paper, on outlining the general approach of this research project.

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تاریخ انتشار 2007