I546 Music Information Processing: Symbolic

Credits: 3

This course deals with both methodology and specific applications that attempt to algorithmically annotate, understand, recognize, and categorize music in symbolic (score like) form. Particular applications will include key finding, harmonic analysis, note spelling, rhythm recognition, meter induction, piano fingering, and various classification problems such as genre or composer identification. The methodology we will employ will be probabilistic and will include ideas from Machine Learning such as optimal classifiers, hidden Markov models, and Bayesian networks. Students will have computing assignments, present papers, and be expected to implement solutions to problems using a high-level language such as R or Matlab.

  • Course History

      Spring 2016

      Instructor: Yupeng Gu
      Time: 2:30PM-3:45PM Mon, Wed
      Location: Student Building, Room 231

      Fall 2011

      Instructor: Christopher Raphael
      Time: 1:00PM-2:15PM Tue, Thu
      Location: Music Library, Room 340