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For music signal segmentation, an 11-stage tree-structured filter bank that leads to wavelet packet analysis was designed and implemented. The tree-structured filter bank has sufficient frequency resolution over a wide range of frequencies, while the time resolution at high frequencies satisfies the minimum time resolution for the human ear. To improve selectivity, a new family of quadrature mirror filters (QMFs) with a narrow transition region and a low reconstruction error was implemented.
Author (s): Bobrek, Miljko;
Koch, Daniel B.;
Affiliation:
Department of Electrical Engineering, The University of Tennessee, Knoxville, TN
(See document for exact affiliation information.)
Publication Date:
1998-05-06
DOI:
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Bobrek, Miljko; Koch, Daniel B.; 1998; Music Signal Segmentation Using Tree-Structured Filter Banks [PDF]; Department of Electrical Engineering, The University of Tennessee, Knoxville, TN; Paper ; Available from: https://aes.org/publications/elibrary-page/?id=12145
Bobrek, Miljko; Koch, Daniel B.; Music Signal Segmentation Using Tree-Structured Filter Banks [PDF]; Department of Electrical Engineering, The University of Tennessee, Knoxville, TN; Paper ; 1998 Available: https://aes.org/publications/elibrary-page/?id=12145
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