Music classification based on melodic similarity with dynamic time warping
- Resource Type
- Conference
- Authors
- Yu, Huijia; Henriquez, Isolda
- Source
- 2013 IEEE International Conference on Computational Intelligence and Computing Research Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on. :1-6 Dec, 2013
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Standards
Hidden Markov models
Rhythm
Conferences
Computational intelligence
Feature extraction
music classification
dynamic time warping
melodic similarity
- Language
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.