Summary: 4004 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 55, NO. 8, AUGUST 2007
Underdetermined Anechoic Blind Source Separation
via `q-Basis-Pursuit With q < 1
Rayan Saab, Student Member, IEEE, Özgür Yilmaz, Member, IEEE, Martin J. McKeown, and
Rafeef Abugharbieh, Member, IEEE
Abstract--In this paper, we address the problem of underdeter-
mined blind source separation (BSS) of anechoic speech mixtures.
We propose a demixing algorithm that exploits the sparsity of
certain time-frequency expansions of speech signals. Our algo-
rithm merges -basis-pursuit with ideas based on the degenerate
unmixing estimation technique (DUET) [Yilmaz and Rickard,
"Blind Source Separation of Speech Mixtures via Time-Frequency
Masking," IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 52,
no. 7, pp. 1830­1847, July 2004]. There are two main novel compo-
nents to our approach: 1) our algorithm makes use of all available
mixtures in the anechoic scenario where both attenuations and
arrival delays between sensors are considered, without imposing
any structure on the microphone positions, and 2) we illustrate
experimentally that the separation performance is improved when
one uses -basis-pursuit with 1 compared to the = 1

Source: Abugharbieh, Rafeef - Department of Electrical and Computer Engineering, University of British Columbia

Collections: Biology and Medicine; Computer Technologies and Information Sciences