By Topic

Solving permutation problem in frequency-domain blind source separation using microphone sub-arrays

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)
Wanlong Li ; Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan ; Ju Liu ; Jun Du ; Shuzhong Bai

Blind source separation for convolutive mixtures can be solved effectively in the frequency domain where independent component analysis is performed in each frequency independently. However, the permutation problem arises: the permutation ambiguity of ICA in each frequency bin should be aligned so that a separated signal in the time-domain contains frequency components of the same source signal. In this paper, we present a new method for solving the permutation problem using microphone sub-arrays. It is based on the combination of two approaches: direction of arrival (DOA) estimation for sources and the inter-frequency correlation of signal envelopes. First, DOA estimation is performed using microphone sub-arrays so that the permutation problem is solved more robustly in low frequencies. Second, we exploit the correlation between the adjacent bins to fix the permutation for the remaining frequencies. Experimental results show that the proposed method provided a more robust solution to the permutation problem in a real acoustic environment.

Published in:

Neural Networks and Signal Processing, 2008 International Conference on

Date of Conference:

7-11 June 2008