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
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