Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions : Survey and Analysis

Publication: Research - peer-reviewJournal article – Annual report year: 2007

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@article{e7a0e92340024951949dea5d7a55c0bb,
title = "Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions",
author = "Hansen, {Per Christian} and Jensen, {Søren Holdt}",
year = "2007",
doi = "10.1155/2007/92953",
volume = "2007",
pages = "092953",
journal = "EURASIP Journal on Advances in Signal Processing",
issn = "1110-8657",

}

RIS

TY - JOUR

T1 - Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

T2 - Survey and Analysis

A1 - Hansen,Per Christian

A1 - Jensen,Søren Holdt

AU - Hansen,Per Christian

AU - Jensen,Søren Holdt

PY - 2007

Y1 - 2007

N2 - We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated with working Matlab code and applications in speech processing.

AB - We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated with working Matlab code and applications in speech processing.

UR - http://www2.imm.dtu.dk/pubdb/p.php?4875

U2 - 10.1155/2007/92953

DO - 10.1155/2007/92953

JO - EURASIP Journal on Advances in Signal Processing

JF - EURASIP Journal on Advances in Signal Processing

SN - 1110-8657

VL - 2007

SP - 092953

ER -