• Title of article

    USING CLASSIFICATION ALGORITHMS FOR TURKISH MUSIC MAKAM RECOGNITION

  • Author/Authors

    öztürk, övünç manisa celal bayar üniversitesi - bilgisayar mühendisliği şehit prof. dr. ilhan varank kampüsü, MANİSA, Turkey , abidin, didem manisa celal bayar üniversitesi - bilgisayar mühendisliği şehit prof. dr. ilhan varank kampüsü, MANİSA, Turkey , özacar, tuğba manisa celal bayar üniversitesi - bilgisayar mühendisliği şehit prof. dr. ilhan varank kampüsü, MANİSA, Turkey

  • From page
    377
  • To page
    393
  • Abstract
    Turkish Music pieces are used in various studies including makam recognition in computational music domain. Turkish Music pieces offer a rich content to the researchers because of their different makam properties. SymbTr is one of the most referred Turkish Music data sets in this area. In this study, the pieces from SymbTr data set belonging to 13 makams are used to execute 10 different machine learning algorithms for makam recognition and the performances of these algorithms are evaluated. These algorithms were executed on WEKA application environment and the performances in makam recognition were obtained with F-measure and recall metrics. The machine learning algorithms performed between 82% and 88%.
  • Keywords
    Machine learning algorithms , Makam recognition , SymbTr , WEKA
  • Journal title
    Selcuk University Journal Of The Engineering, Science an‎d Technology
  • Journal title
    Selcuk University Journal Of The Engineering, Science an‎d Technology
  • Record number

    2689062