VExPat: An Analysis Tool for the Discovery of Musical Patterns

نویسندگان

  • Hugo Santana
  • Márcio Dahia
  • Ernesto Lima
  • Geber Ramalho
چکیده

This paper describes VExPat, a system that assists on the task of extracting patterns from musical sequences. Although there are known algorithms that perform this task efficiently, none of the existing analysis tools provide this functionality. Furthermore, VExPat provides a user-friendly interface, with score visualization and musical execution facilities, allowing its use even by computer non-specialists, which is the case for a large number of musicologists. Another innovation is the use of MusicXML, an extensible and user-accessible format for representation of music. Finally, it is proposed an architecture for dealing with different internal music representations, and also an object oriented model for a score viewer, both based on MusicXML.

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تاریخ انتشار 2003