DocumentCode
2149894
Title
Degenerate Unmixing Estimation Technique using the Constant Q Transform
Author
Rafii, Zafar ; Pardo, Bryan
Author_Institution
EECS Dept., Northwestern Univ., Evanston, IL, USA
fYear
2011
fDate
22-27 May 2011
Firstpage
217
Lastpage
220
Abstract
The Degenerate Unmixing Estimation Technique (DUET) is a Blind Source Separation (BSS) algorithm for stereo audio. DUET depends on an amplitude-phase 2d histogram built from the differences between the two channels, where peaks in the histogram indicate sources in the mixture. If peaks overlap, separation becomes unfeasible. This is often the case for music mixtures. We propose to improve peak separation by building histograms from time-frequency representations based on the Constant Q Transform (CQT) instead of the Fourier Transform (FT). The CQT has a logarithmic frequency resolution matching the geometrically spaced notes of the Western music scale. We also adaptively resize histogram bins and use Wiener filtering to improve peak resolving and source reconstruction. Results on mixtures of harmonic musical instruments show improvement in separation, especially at low frequencies and for closely spaced sources.
Keywords
Wiener filters; audio signal processing; blind source separation; channel estimation; harmonic analysis; music; time-frequency analysis; DUET; Fourier transform; Western music scale; Wiener filtering; adaptively resize histogram bins; amplitude-phase 2D histogram; blind source separation algorithm; constant Q transform; geometrically spaced note; harmonic musical instrument; histogram building; logarithmic frequency resolution matching; music mixture; peak separation; source reconstruction; spaced sources; stereo audio; time-frequency representation; unmixing estimation technique; Estimation; Histograms; Instruments; Source separation; Speech; Time frequency analysis; Transforms; Blind Source Separation; Constant Q Transform; Degenerate Unmixing Estimation Technique;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location
Prague
ISSN
1520-6149
Print_ISBN
978-1-4577-0538-0
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2011.5946379
Filename
5946379
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