Blind source separation based on independent vector analysis using feed-forward network
This paper presents an algorithm that employs a feed-forward (FF) network on each bin as an unmixing system in the framework of independent vector analysis (IVA) to effectively separate highly reverberated mixtures with the exploitation of inter-frequency dependencies of each source signal. Furtherm...
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| Published in | Neurocomputing (Amsterdam) Vol. 74; no. 17; pp. 3713 - 3715 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.10.2011
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| Subjects | |
| Online Access | Get full text |
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| Abstract | This paper presents an algorithm that employs a feed-forward (FF) network on each bin as an unmixing system in the framework of independent vector analysis (IVA) to effectively separate highly reverberated mixtures with the exploitation of inter-frequency dependencies of each source signal. Furthermore, to avoid whitening of unmixed source signals due to the use of the FF unmixing network, we derive a learning algorithm for the network based on the extended non-holonomic constraint and the minimal distortion principle. Experiments show that the proposed method delivers better separation performance than the conventional IVA and the FF independent component analysis methods. |
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| AbstractList | This paper presents an algorithm that employs a feed-forward (FF) network on each bin as an unmixing system in the framework of independent vector analysis (IVA) to effectively separate highly reverberated mixtures with the exploitation of inter-frequency dependencies of each source signal. Furthermore, to avoid whitening of unmixed source signals due to the use of the FF unmixing network, we derive a learning algorithm for the network based on the extended non-holonomic constraint and the minimal distortion principle. Experiments show that the proposed method delivers better separation performance than the conventional IVA and the FF independent component analysis methods. |
| Author | Oh, Myungwoo Park, Hyung-Min |
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| CitedBy_id | crossref_primary_10_1016_j_neucom_2019_04_030 crossref_primary_10_1016_j_patcog_2023_109376 crossref_primary_10_1016_j_neucom_2015_12_040 crossref_primary_10_1016_j_neucom_2019_07_022 crossref_primary_10_1109_ACCESS_2020_2985842 crossref_primary_10_1007_s11063_017_9741_0 crossref_primary_10_1587_transfun_E98_A_2325 |
| Cites_doi | 10.1109/TASL.2006.872618 |
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| Copyright | 2011 Elsevier B.V. |
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| Keywords | Feed-forward network Blind source separation Independent component analysis |
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| References | Hyvärinen, Karhunen, Oja (bib2) 2001 Sawada, Mukai, Araki, Makino (bib6) 2001 Araki, Makino, Nishikawa, Saruwatari (bib1) 2001 Kim, Attias, Lee, Lee (bib4) 2007; 15 Matsuoka, Nakashima (bib5) 2001 Kim, Tashev, Acero (bib3) 2010 Kim (10.1016/j.neucom.2011.06.008_bib4) 2007; 15 Hyvärinen (10.1016/j.neucom.2011.06.008_bib2) 2001 Matsuoka (10.1016/j.neucom.2011.06.008_bib5) 2001 Sawada (10.1016/j.neucom.2011.06.008_bib6) 2001 Kim (10.1016/j.neucom.2011.06.008_bib3) 2010 Araki (10.1016/j.neucom.2011.06.008_bib1) 2001 |
| References_xml | – volume: 15 start-page: 70 year: 2007 end-page: 79 ident: bib4 article-title: Blind source separation exploiting higher-order frequency dependencies publication-title: IEEE Transactions on Audio, Speech, and Language Processing contributor: fullname: Lee – start-page: 2678 year: 2010 end-page: 2681 ident: bib3 article-title: Reverberated speech signal separation based on regularized subband feedforward ICA and instantaneous direction of arrival publication-title: Proceedings of the ICASSP contributor: fullname: Acero – start-page: 722 year: 2001 end-page: 727 ident: bib5 article-title: Minimal distortion principle for blind source separation publication-title: Proceedings of the International Conference on ICA and BSS contributor: fullname: Nakashima – year: 2001 ident: bib2 article-title: Independent Component Analysis contributor: fullname: Oja – start-page: 2737 year: 2001 end-page: 2740 ident: bib1 article-title: Fundamental limitation of frequency domain blind source separation for convolutive mixture of speech publication-title: Proceedings of the ICASSP contributor: fullname: Saruwatari – start-page: 663 year: 2001 end-page: 668 ident: bib6 article-title: A polar-coordinate based activation function for frequency domain blind source separation publication-title: Proceedings of the International Conference on ICA and BSS contributor: fullname: Makino – year: 2001 ident: 10.1016/j.neucom.2011.06.008_bib2 contributor: fullname: Hyvärinen – start-page: 2737 year: 2001 ident: 10.1016/j.neucom.2011.06.008_bib1 article-title: Fundamental limitation of frequency domain blind source separation for convolutive mixture of speech contributor: fullname: Araki – start-page: 2678 year: 2010 ident: 10.1016/j.neucom.2011.06.008_bib3 article-title: Reverberated speech signal separation based on regularized subband feedforward ICA and instantaneous direction of arrival contributor: fullname: Kim – start-page: 663 year: 2001 ident: 10.1016/j.neucom.2011.06.008_bib6 article-title: A polar-coordinate based activation function for frequency domain blind source separation contributor: fullname: Sawada – start-page: 722 year: 2001 ident: 10.1016/j.neucom.2011.06.008_bib5 article-title: Minimal distortion principle for blind source separation contributor: fullname: Matsuoka – volume: 15 start-page: 70 year: 2007 ident: 10.1016/j.neucom.2011.06.008_bib4 article-title: Blind source separation exploiting higher-order frequency dependencies publication-title: IEEE Transactions on Audio, Speech, and Language Processing doi: 10.1109/TASL.2006.872618 contributor: fullname: Kim |
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| SubjectTerms | Algorithms Blind source separation Blinds Distortion Exploitation Feed-forward network Independent component analysis Learning Networks Separation Vector analysis |
| Title | Blind source separation based on independent vector analysis using feed-forward network |
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