Information Retrieval in Metal Music Sub Genres

Abstract

Digital music platforms use meta-data based information retrieval systems for offering songs to users for their own taste of music. According to this system, songs that are labeled by other users are compared to songs that user listened and similar labeled songs are retrived in the process. In this situtation, information retrieval is independent from song content and subjective. To achieve objectivity, content based information retrieval systems are needed. In this study, a content-based music retrieval system based on one dimensional local binary pattern features which are extracted from audio data is proposed. Instead of retrieving different music genres, retrieval is applied on metal music sub-genres which have not been studied before and results are reported.