Music classification based on melodic similarity with dynamic time warping

Melodic similarity is very important for analysis and classification of classical music. The difficulties to measure the melodic similarity are mainly structural complexity and melodic variations. It is more difficult to use machine learning techniques to measure it automatically. In this paper we use a hybrid of two methods: numbered musical notation and dynamic time warping. Several classic music pieces are used to demonstrate effectiveness of our method. This method can be directly extended to measure the melodic similarity of the other types of music.