Recognition of isolated musical patterns in the context of Greek traditional music

Recognition of pre-defined musical patterns in the context of Greek Traditional Music is very useful to researchers in Musicology and Ethnomusicology. This paper presents an efficient method for recognizing isolated musical patterns played by Creek Traditional Clarinet, in a monophonic environment. The Discrete Time Wavelet Transform of the signal is calculated. The highest scales, along with the lowpass residue of the Wavelet Transform, are treated as signals and the spectrogram of each one of them is calculated. The spectrograms are in turn treated as 2-D images. A number of translation and scaling invariant moments are then computed for the resulting images. These moments are used as features, and turn out to cluster around certain points in the corresponding multidimensional feature space, for the various musical patterns. Tree-like structured classification procedure is then adopted for classification. A few clusters correspond to more than one musical pattern. In such case a Dynamic Time Warping procedure is employed to determine the specific pattern.