Winter S, Kellermann W, Sawada H, Makino S (2007)
Publication Language: English
Publication Type: Book chapter / Article in edited volumes
Publication year: 2007
Publisher: Springer
Edited Volumes: Blind Speech Separation
Series: Signals and Communication Technology
City/Town: Dordrecht
Pages Range: 271-304
ISBN: 978-1-4020-6479-1
DOI: 10.1007/978-1-4020-6479-1_10
In this chapter we present a complete solution for underdetermined blind source separation (BSS) of convolutive speech mixtures based on two stages. In the first stage, the mixing system is estimated, for which we employ hierarchical clustering. Based on the estimated mixing system, the source signals are estimated in the second stage. The solution for the second stage utilizes the common assumption of independent and identically distributed sources. Modeling the sources by a Laplacian distribution leads to ℓ1-norm minimization.©Springer
APA:
Winter, S., Kellermann, W., Sawada, H., & Makino, S. (2007). Underdetermined blind source separation of convolutive mixtures by hierarchical clustering and L1-norm minimization. In S. Makino, Te-Won Lee, H. Sawada (Eds.), Blind Speech Separation. (pp. 271-304). Dordrecht: Springer.
MLA:
Winter, Stefan, et al. "Underdetermined blind source separation of convolutive mixtures by hierarchical clustering and L1-norm minimization." Blind Speech Separation. Ed. S. Makino, Te-Won Lee, H. Sawada, Dordrecht: Springer, 2007. 271-304.
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