Using Back Propagation Model to Design a MIDI Music Classification System

Abstract

The main purpose of this paper is to investigate how to develop an effective classification system that can first categorize the characteristics in MIDI music files and then search similar music in the Internet. In this system, back propagation network is applied to train and categorize the characteristics in MIDI music. Many search engines now can provide efficient ways to search music. However, those search engines only search the files by the names of music, and cannot categorize and compare the music according to the characteristics of music. In this paper, we select representative songs of eight specific music categories to construct a module that can identify the types of music by means of back propagation network. We introduce the theoretical basis of music classification and present the experiment results to validate the effectiveness of the proposed model.