N-gram based Statistical Makam Detection on Makam Music in Turkey using Symbolic Data”, submitted to ISMIR

This work studies the effect of different score representa-tions and the potential of n-grams in makam classification for traditional makam music in Turkey. While makams are defined with various characteristics including a dis-tinct set of pitches, pitch hierarchy, melodic direction, typical phrases and typical makam transitions, such cha-racteristics result in certain n-gram distributions which can be used for makam detection effectively. 13 popular makams, some of which are very similar to each other, are used in this study. Using the leave-one-out strategy, makam models are created statistically and tested against the left out music piece. Tests indicate that n-gram based statistical modeling and perplexity based similarity metric can be effectively used for makam detection. However the main dimension that cannot be captured is the overall progression which is the most unique feature for classifi-cation of close makams that uses the same scale notes as well as the same tonic. 1