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Extracting Sound Objects by Independent Subspace Analysis

In this paper we present a scheme for unsupervised extraction of sound objects or sources from a single recording containing a mixture of sounds. The separation/extraction procedure is performed by orthogonal projection of the mixed sound onto sub-spaces that are derived by clustering of transform coefficients, such as coefficients obtained by PCA or ICA. The clustering step reveals a residual non-linear grouping structure of the signal that is omitted by the linear transform. To achieve independence we are searching for partitioning that maximizes the mutual information between a component and a set to which it belongs. This information is obtained by considering a pairwise distance measure among all coefficients. Source separation experiments are reported in the paper.

Author: Dubnov, Shlomo
Affiliation: Department of Communication Systems Engineering, Ben Gurion University, Beer Sheva, Israel
AES Conference:22nd International Conference: Virtual, Synthetic, and Entertainment Audio (June 2002)
Paper Number:000252 Import into BibTeX
Subject:Virtual, Synthetic and Entertainment Audio

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E-Library Location: (CD aes19)   /intl2002/2002es06/000252.pdf

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