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Underdetermined convolutive blind source separation via time-frequency masking

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Underdetermined convolutive blind source separation via time-frequency masking

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Title: Underdetermined convolutive blind source separation via time-frequency masking
Author: Reju, Vaninirappuputhenpurayil Gopalan; Koh, Soo Ngee; Soon, Ing Yann
Copyright year: 2009
Abstract: In this paper, we consider the problem of separation of unknown number of sources from their underdetermined convolutive mixtures via time-frequency (TF) masking. We propose two algorithms, one for the estimation of the masks which are to be applied to the mixture in the TF domain for the separation of signals in the frequency domain, and the other for solving the permutation problem. The algorithm for mask estimation is based on the concept of angles in complex vector space. Unlike the previously reported methods, the algorithm does not require any estimation of the mixing matrix or the source positions for mask estimation. The algorithm clusters the mixture samples in the TF domain based on the Hermitian angle between the sample vector and a reference vector using the well known k -means or fuzzy c -means clustering algorithms. The membership functions so obtained from the clustering algorithms are directly used as the masks. The algorithm for solving the permutation problem clusters the estimated masks by using k-means clustering of small groups of nearby masks with overlap. The effectiveness of the algorithm in separating the sources, including collinear sources, from their underdetermined convolutive mixtures obtained in a real room environment, is demonstrated.
Subject: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing.
Type: Journal Article
Series/ Journal Title: IEEE transactions on audio, speech, and language processing
School: School of Electrical and Electronic Engineering
Rights: © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [DOI: http://dx.doi.org/10.1109/TASL.2009.2024380].
Version: Accepted version

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