Journal article
Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions: Survey and Analysis
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.
Language: | English |
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Publisher: | Springer International Publishing |
Year: | 2007 |
Pages: | 1-24 |
ISSN: | 16876180 , 16876172 , 16870433 and 11108657 |
Types: | Journal article |
DOI: | 10.1155/2007/92953 |
ORCIDs: | Hansen, Per Christian |