Using gaussian potential function for underdetermined blind sources separation based on DUET

Authors:
Ye Zhang;Kang Cao;Kangrui Wu;Tenglong Yu
Affiliations:
Department of Electronic and Information Engineering, Nanchang University, Nanchang, China;Department of Electronic and Information Engineering, Nanchang University, Nanchang, China;Department of Electronic and Information Engineering, Nanchang University, Nanchang, China;Department of Electronic and Information Engineering, Nanchang University, Nanchang, China
Venue:
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Year:
2012

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Abstract

The DUET algorithm is a typical underdetermined blind source separation method, while the estimation of mixing parameters is an important part of DUET algorithm. In the presence of noise, a robust DUET algorithm is proposed to estimate the mixing parameters, i.e. the delay and attenuation between microphones and sources. The mixing parameters can be obtained by estimating the local maximum of the Gaussian potential function. Then the binary time---frequency mask can be constructed to recover the source signals by using the mixing parameters. From the experimental results on audio mixtures, the proposed algorithm is simple and highly effective, and the accuracy of the estimated source signals is higher than that of the original DUET algorithm.