'The Society of Digital Information and Wireless Communications (SDIWC)'
Abstract
For decades now, scientific community are involved in various works to automate the human process of recognizing different types of music using different elements for example different instruments used. These efforts would imitate the human method of recognizing the music by considering every essential component of the songs from artist voice, melody of the music through to the type of instruments used. Various approaches or mechanisms are introduced and developed to automate the classification process since then. The results of these studies so far have been remarkable yet can still be improved. The aim of this research is to investigate Artificial Immune System (AIS) domain by focusing on the modified AIS-based classifier to solve this problem where the focuses are the censoring and monitoring modules. In this highlight, stages of music recognition are emphasized where feature extraction, feature selection, and feature classification processes are explained. Comparison of performances between proposed classifier and WEKA application is discussed. Almost 20 to 30 percent of classification accuracies are increased in this study
