By Topic

Audio source separation of convolutive mixtures

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
$33 $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

2 Author(s)
N. Mitianoudis ; Electron. Eng. Dept., Queen Mary Univ. of London, UK ; M. E. Davies

The problem of separation of audio sources recorded in a real world situation is well established in modern literature. A method to solve this problem is blind source separation (BSS) using independent component analysis (ICA). The recording environment is usually modeled as convolutive. Previous research on ICA of instantaneous mixtures provided solid background for the separation of convolved mixtures. The authors revise current approaches on the subject and propose a fast frequency domain ICA framework, providing a solution for the apparent permutation problem encountered in these methods.

Published in:

IEEE Transactions on Speech and Audio Processing  (Volume:11 ,  Issue: 5 )