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S. Dubnov, "Extracting Sound Objects by Independent Subspace Analysis," Paper 000252, (2002 June.). doi: S. Dubnov, "Extracting Sound Objects by Independent Subspace Analysis," Paper 000252, (2002 June.). doi:
Abstract: 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.

@article{dubnov2002extracting,
author={dubnov, shlomo},
journal={journal of the audio engineering society},
title={extracting sound objects by independent subspace analysis},
year={2002},
volume={},
number={},
pages={},
doi={},
month={june},} @article{dubnov2002extracting,
author={dubnov, shlomo},
journal={journal of the audio engineering society},
title={extracting sound objects by independent subspace analysis},
year={2002},
volume={},
number={},
pages={},
doi={},
month={june},
abstract={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.},}

TY - paper
TI - Extracting Sound Objects by Independent Subspace Analysis
SP - EP -
AU - Dubnov, Shlomo
PY - 2002
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - June 2002 TY - paper
TI - Extracting Sound Objects by Independent Subspace Analysis
SP - EP -
AU - Dubnov, Shlomo
PY - 2002
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - June 2002
AB - 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.