An automated method for classifying music signals into genres is proposed. Up to three genres are assigned to each example along with a measure of the degree of influence. The method is based on a structure formed by taxonomy of four hierarchical layers, with 29 genres in the lowest layer and 10 target genres in the higher layers. In more than 77% of the cases there was successful classification. The computational effort is sufficiently low that this method could be used in real time.

Authors: Barbedo, Jayme Garcia Arnal; Lopes, Amauri
Affiliation: Department of Communications, FEEC, UNICAMP, 13.083-852, Campinas, SP, Brazil
JAES Volume 56 Issue 7/8 pp. 560-568; July 2008
Publication Date: August 21, 2008 Import into BibTeX
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=14400

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location: (CD JAES56)   /jaes56/7/pg560.pdf

Start a discussion about this paper!