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Neurocomputing
Article . 2008 . Peer-reviewed
License: Elsevier TDM
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Partial separation method for solving permutation problem in frequency domain blind source separation of speech signals

Authors: Reju, Vaninirappuputhenpurayil Gopalan; Koh, Soo Ngee; Soon, Ing Yann;

Partial separation method for solving permutation problem in frequency domain blind source separation of speech signals

Abstract

This paper addresses the well known permutation problem in frequency domain blind source separation. The proposed method uses correlation between two signals in each DFT bin to solve the permutation problem. One of the signals is partially separated by a time domain blind source separation method and the other is obtained by the frequency domain blind source separation method. Two different ways of configuring the time and frequency domain blocks, i.e., in parallel or cascade, have been studied. The cascaded configuration not only achieves a better separation performance but also reduces the computational cost as compared to the parallel configuration.

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Keywords

:Engineering::Electrical and electronic engineering::Electronic systems::Signal processing [DRNTU], DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing, 530, 004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Average
Top 10%
Top 10%
Green
bronze