Separation of Mixed Audio Signals by Decomposing Hilbert Spectrum with Modified EMD
Summary :
The Hilbert transformation together with empirical mode decomposition (EMD) produces Hilbert spectrum (HS) which is a fine-resolution time-frequency representation of any nonlinear and non-stationary signal. The EMD decomposes the mixture signal into some oscillatory components each one is called intrinsic mode function (IMF). Some modification of the conventional EMD is proposed here. The instantaneous frequency of every real valued IMF component is computed with Hilbert transformation. The HS is constructed by arranging the instantaneous frequency spectra of IMF components. The HS of the mixture signal is decomposed into subspaces corresponding to the component sources. The decomposition is performed by applying independent component analysis (ICA) and Kulback-Leibler divergence based K-means clustering on the selected number of bases derived from HS of the mixture. The time domain source signals are assembled by applying some post processing on the subspaces. We have produced experimental results using the proposed separation technique.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E89-A No.3 pp.727-734
- Publication Date
- 2006/03/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e89-a.3.727
- Type of Manuscript
- Special Section PAPER (Special Section on Multidimensional Signal Processing and Its Application)
- Category
- Speech/Audio Processing
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Md. Khademul Islam MOLLA, Keikichi HIROSE, Nobuaki MINEMATSU, "Separation of Mixed Audio Signals by Decomposing Hilbert Spectrum with Modified EMD" in IEICE TRANSACTIONS on Fundamentals,
vol. E89-A, no. 3, pp. 727-734, March 2006, doi: 10.1093/ietfec/e89-a.3.727.
Abstract: The Hilbert transformation together with empirical mode decomposition (EMD) produces Hilbert spectrum (HS) which is a fine-resolution time-frequency representation of any nonlinear and non-stationary signal. The EMD decomposes the mixture signal into some oscillatory components each one is called intrinsic mode function (IMF). Some modification of the conventional EMD is proposed here. The instantaneous frequency of every real valued IMF component is computed with Hilbert transformation. The HS is constructed by arranging the instantaneous frequency spectra of IMF components. The HS of the mixture signal is decomposed into subspaces corresponding to the component sources. The decomposition is performed by applying independent component analysis (ICA) and Kulback-Leibler divergence based K-means clustering on the selected number of bases derived from HS of the mixture. The time domain source signals are assembled by applying some post processing on the subspaces. We have produced experimental results using the proposed separation technique.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e89-a.3.727/_p
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@ARTICLE{e89-a_3_727,
author={Md. Khademul Islam MOLLA, Keikichi HIROSE, Nobuaki MINEMATSU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Separation of Mixed Audio Signals by Decomposing Hilbert Spectrum with Modified EMD},
year={2006},
volume={E89-A},
number={3},
pages={727-734},
abstract={The Hilbert transformation together with empirical mode decomposition (EMD) produces Hilbert spectrum (HS) which is a fine-resolution time-frequency representation of any nonlinear and non-stationary signal. The EMD decomposes the mixture signal into some oscillatory components each one is called intrinsic mode function (IMF). Some modification of the conventional EMD is proposed here. The instantaneous frequency of every real valued IMF component is computed with Hilbert transformation. The HS is constructed by arranging the instantaneous frequency spectra of IMF components. The HS of the mixture signal is decomposed into subspaces corresponding to the component sources. The decomposition is performed by applying independent component analysis (ICA) and Kulback-Leibler divergence based K-means clustering on the selected number of bases derived from HS of the mixture. The time domain source signals are assembled by applying some post processing on the subspaces. We have produced experimental results using the proposed separation technique.},
keywords={},
doi={10.1093/ietfec/e89-a.3.727},
ISSN={1745-1337},
month={March},}
Copy
TY - JOUR
TI - Separation of Mixed Audio Signals by Decomposing Hilbert Spectrum with Modified EMD
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 727
EP - 734
AU - Md. Khademul Islam MOLLA
AU - Keikichi HIROSE
AU - Nobuaki MINEMATSU
PY - 2006
DO - 10.1093/ietfec/e89-a.3.727
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E89-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2006
AB - The Hilbert transformation together with empirical mode decomposition (EMD) produces Hilbert spectrum (HS) which is a fine-resolution time-frequency representation of any nonlinear and non-stationary signal. The EMD decomposes the mixture signal into some oscillatory components each one is called intrinsic mode function (IMF). Some modification of the conventional EMD is proposed here. The instantaneous frequency of every real valued IMF component is computed with Hilbert transformation. The HS is constructed by arranging the instantaneous frequency spectra of IMF components. The HS of the mixture signal is decomposed into subspaces corresponding to the component sources. The decomposition is performed by applying independent component analysis (ICA) and Kulback-Leibler divergence based K-means clustering on the selected number of bases derived from HS of the mixture. The time domain source signals are assembled by applying some post processing on the subspaces. We have produced experimental results using the proposed separation technique.
ER -
English
