377 research outputs found

    Fast Dictionary Learning for Sparse Representations of Speech Signals

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    © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Published version: IEEE Journal of Selected Topics in Signal Processing 5(5): 1025-1031, Sep 2011. DOI: 10.1109/JSTSP.2011.2157892

    ANALYSIS-BASED SPARSE RECONSTRUCTION WITH SYNTHESIS-BASED SOLVERS

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    © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

    Audio Source Separation Using Sparse Representations

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    This is the author's final version of the article, first published as A. Nesbit, M. G. Jafari, E. Vincent and M. D. Plumbley. Audio Source Separation Using Sparse Representations. In W. Wang (Ed), Machine Audition: Principles, Algorithms and Systems. Chapter 10, pp. 246-264. IGI Global, 2011. ISBN 978-1-61520-919-4. DOI: 10.4018/978-1-61520-919-4.ch010file: NesbitJafariVincentP11-audio.pdf:n\NesbitJafariVincentP11-audio.pdf:PDF owner: markp timestamp: 2011.02.04file: NesbitJafariVincentP11-audio.pdf:n\NesbitJafariVincentP11-audio.pdf:PDF owner: markp timestamp: 2011.02.04The authors address the problem of audio source separation, namely, the recovery of audio signals from recordings of mixtures of those signals. The sparse component analysis framework is a powerful method for achieving this. Sparse orthogonal transforms, in which only few transform coefficients differ significantly from zero, are developed; once the signal has been transformed, energy is apportioned from each transform coefficient to each estimated source, and, finally, the signal is reconstructed using the inverse transform. The overriding aim of this chapter is to demonstrate how this framework, as exemplified here by two different decomposition methods which adapt to the signal to represent it sparsely, can be used to solve different problems in different mixing scenarios. To address the instantaneous (neither delays nor echoes) and underdetermined (more sources than mixtures) mixing model, a lapped orthogonal transform is adapted to the signal by selecting a basis from a library of predetermined bases. This method is highly related to the windowing methods used in the MPEG audio coding framework. In considering the anechoic (delays but no echoes) and determined (equal number of sources and mixtures) mixing case, a greedy adaptive transform is used based on orthogonal basis functions that are learned from the observed data, instead of being selected from a predetermined library of bases. This is found to encode the signal characteristics, by introducing a feedback system between the bases and the observed data. Experiments on mixtures of speech and music signals demonstrate that these methods give good signal approximations and separation performance, and indicate promising directions for future research

    SEPARATING SOURCES FROM SEQUENTIALLY ACQUIRED MIXTURES OF HEART SIGNALS

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    © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

    Audio Inpainting

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    (c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Published version: IEEE Transactions on Audio, Speech and Language Processing 20(3): 922-932, Mar 2012. DOI: 10.1090/TASL.2011.2168211

    A CONSTRAINED MATCHING PURSUIT APPROACH TO AUDIO DECLIPPING

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    © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

    Sequential blind source separation based exclusively on second-order statistics developed for a class of periodic signals

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    A sequential algorithm for the blind separation of a class of periodic source signals is introduced in this paper. The algorithm is based only on second-order statistical information and exploits the assumption that the source signals have distinct periods. Separation is performed by sequentially converging to a solution which in effect diagonalizes the output covariance matrix constructed at a lag corresponding to the fundamental period of the source we select, the one with the smallest period. Simulation results for synthetic signals and real electrocardiogram recordings show that the proposed algorithm has the ability to restore statistical independence, and its performance is comparable to that of the equivariant adaptive source separation (EASI) algorithm, a benchmark high-order statistics-based sequential algorithm with similar computational complexity. The proposed algorithm is also shown to mitigate the limitation that the EASI algorithm can separate at most one Gaussian distributed source. Furthermore, the steady-state performance of the proposed algorithm is compared with that of EASI and the block-based second-order blind identification (SOBI) method

    The role of inflammatory pathway genetic variation on maternal metabolic phenotypes during pregnancy

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    BACKGROUND: Since mediators of inflammation are associated with insulin resistance, and the risk of developing diabetes mellitus and gestational diabetes, we hypothesized that genetic variation in members of the inflammatory gene pathway impact glucose levels and related phenotypes in pregnancy. We evaluated this hypothesis by testing for association between genetic variants in 31 inflammatory pathway genes in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) cohort, a large multiethnic multicenter study designed to address the impact of glycemia less than overt diabetes on pregnancy outcome. RESULTS: Fasting, 1-hour, and 2-hour glucose, fasting and 1-hour C-peptide, and HbA1c levels were measured in blood samples obtained from HAPO participants during an oral glucose tolerance test at 24-32 weeks gestation. We tested for association between 458 SNPs mapping to 31 genes in the inflammatory pathway and metabolic phenotypes in 3836 European ancestry and 1713 Thai pregnant women. The strongest evidence for association was observed with TNF alpha and HbA1c (rs1052248; 0.04% increase per allele C; p-value = 4.4×10(-5)), RETN and fasting plasma glucose (rs1423096; 0.7 mg/dl decrease per allele A; p-value = 1.1×10(-4)), IL8 and 1 hr plasma glucose (rs2886920; 2.6 mg/dl decrease per allele T; p-value = 1.3×10(-4)), ADIPOR2 and fasting C-peptide (rs2041139; 0.55 ug/L decrease per allele A; p-value = 1.4×10(-4)), LEPR and 1-hour C-peptide (rs1171278; 0.62 ug/L decrease per allele T; p-value = 2.4×10(-4)), and IL6 and 1-hour plasma glucose (rs6954897; -2.29 mg/dl decrease per allele G, p-value = 4.3×10(-4)). CONCLUSIONS: Based on the genes surveyed in this study the inflammatory pathway is unlikely to have a strong impact on maternal metabolic phenotypes in pregnancy although variation in individual members of the pathway (e.g. RETN, IL8, ADIPOR2, LEPR, IL6, and TNF alpha,) may contribute to metabolic phenotypes in pregnant women.The study is funded by grants R01 DK067459, R01-HD34242 and R01-HD34243 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Institute of Diabetes, Digestive, and Kidney Diseases, by the National Center for Research Resources (M01-RR00048, M01-RR00080), and by the American Diabetes Association. RMF is funded by a Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust grant: 085541/Z/08/Z). ATH is employed as a core member of the Peninsula NIHR Clinical Research Facility. Support has also been provided to local field centers by Diabetes UK (RD04/0002756), Kaiser Permanente Medical Center, KK Women's and Children's Hospital, Mater Mother's Hospital, Novo Nordisk, the Myre Sim Fund of the Royal College of Physicians of Edinburgh, and the Howard and Carol Bernick Family Foundation. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Parasites and immunotherapy: with or against?

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    Immunotherapy is a sort of therapy in which antibody or antigen administrates to the patient in order to treat or reduce the severity of complications of disease. This kind of treatment practiced in a wide variety of diseases including infectious diseases, autoimmune disorders, cancers and allergy. Successful and unsuccessful immunotherapeutic strategies have been practiced in variety of parasitic infections. On the other hand parasites or parasite antigens have also been considered for immunotherapy against other diseases such as cancer, asthma and multiple sclerosis. In this paper immunotherapy against common parasitic infections, and also immunotherapy of cancer, asthma and multiple sclerosis with parasites or parasite antigens have been reviewe

    Peripheral T Cell Cytokine Responses for Diagnosis of Active Tuberculosis

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    BACKGROUND: A test for diagnosis of active Tuberculosis (TB) from peripheral blood could tremendously improve clinical management of patients. METHODS: Of 178 prospectively enrolled patients with possible TB, 60 patients were diagnosed with pulmonary and 27 patients with extrapulmonary TB. The frequencies of Mycobacterium tuberculosis (MTB) specific CD4(+) T cells and CD8(+) T cells producing cytokines were assessed using overnight stimulation with purified protein derivate (PPD) or early secretory antigenic target (ESAT)-6, respectively. RESULTS: Among patients with active TB, an increased type 1 cytokine profile consisting of mainly CD4(+) T cell derived interferon (IFN)-γ was detectable. Despite contributing to the cytokine profile as a whole, the independent diagnostic performance of one cytokine producing T cells as well as polyfunctional T cells was poor. IFN-γ/Interleukin(IL)-2 cytokine ratios discriminated best between active TB and other diseases. CONCLUSION: T cells producing one cytokine and polyfunctional T cells have a limited role in diagnosis of active TB. The significant shift from a "memory type" to an "effector type" cytokine profile may be useful for further development of a rapid immune-diagnostic tool for active TB
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