Cart (Loading....) | Create Account
Close category search window
 

Cultural style based music classification of audio signals

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

Music classification based on cultural style is useful for music analysis and has potential applications in retrieval and recommendation systems. In this paper, we present the first attempt to classify audio signals automatically according to their cultural styles, which are characterized by timbre, rhythm, wavelet coefficients and musicology-based features. Machine learning algorithms are employed to investigate the effectiveness of various features on a data set of 1300 music pieces. Experimental results show that the proposed method can achieve an overall accuracy of 86% for six cultural styles, which shows the feasibility of integrating cultural style classification into music retrieval systems.

Published in:

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Date of Conference:

19-24 April 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.