Scheduled System Maintenance:
On Wednesday, July 29th, IEEE Xplore will undergo scheduled maintenance from 7:00-9:00 AM ET (11:00-13:00 UTC). During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Gaussian mixture models for score-informed instrument separation

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

3 Author(s)
Sprechmann, P. ; Univ. of Minnesota, Minneapolis, MN, USA ; Cancela, P. ; Sapiro, G.

A new framework for representing quasi-harmonic signals, and its application to score-informed single channel musical instruments separation, is introduced in this paper. In the proposed approach, the signal's pitch and spectral envelope are modeled separately. The model combines parametric filters enforcing an harmonic structure in the representation, with Gaussian modeling for representing the spectral envelope. The estimation of the signal's model is cast as an inverse problem efficiently solved via a maximum a posteriori expectation-maximization algorithm. The relation of the proposed framework with common non-negative factorization methods is also discussed. The algorithm is evaluated with both real and synthetic instruments mixtures, and comparisons with recently proposed techniques are presented.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Date of Conference:

25-30 March 2012