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A Compressed Sensing Approach to Blind Separation of Speech Mixture Based on a Two-Layer Sparsity Model

Published: 01 May 2013 Publication History

Abstract

This paper discusses underdetermined blind source separation (BSS) using a compressed sensing (CS) approach, which contains two stages. In the first stage we exploit a modified K-means method to estimate the unknown mixing matrix. The second stage is to separate the sources from the mixed signals using the estimated mixing matrix from the first stage. In the second stage a two-layer sparsity model is used. The two-layer sparsity model assumes that the low frequency components of speech signals are sparse on K-SVD dictionary and the high frequency components are sparse on discrete cosine transformation (DCT) dictionary. This model, taking advantage of two dictionaries, can produce effective separation performance even if the sources are not sparse in time-frequency (TF) domain.

Cited By

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  • (2019)"A speech recognizer" a tool to recognize the high clarity speech signal based on existing speech using ISCAAnalog Integrated Circuits and Signal Processing10.1007/s10470-018-1275-598:1(41-58)Online publication date: 1-Jan-2019
  • (2018)Non-stationary sources separation based on maximum likelihood criterion using source temporalspatial modelNeurocomputing10.1016/j.neucom.2017.08.034275:C(341-349)Online publication date: 31-Jan-2018
  • (2018)Novel underdetermined blind source separation algorithm based on compressed sensing and K‐SVDTransactions on Emerging Telecommunications Technologies10.1002/ett.342729:9Online publication date: 7-Sep-2018
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  1. A Compressed Sensing Approach to Blind Separation of Speech Mixture Based on a Two-Layer Sparsity Model

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    cover image IEEE Transactions on Audio, Speech, and Language Processing
    IEEE Transactions on Audio, Speech, and Language Processing  Volume 21, Issue 5
    May 2013
    220 pages

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    IEEE Press

    Publication History

    Published: 01 May 2013

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    • (2019)"A speech recognizer" a tool to recognize the high clarity speech signal based on existing speech using ISCAAnalog Integrated Circuits and Signal Processing10.1007/s10470-018-1275-598:1(41-58)Online publication date: 1-Jan-2019
    • (2018)Non-stationary sources separation based on maximum likelihood criterion using source temporalspatial modelNeurocomputing10.1016/j.neucom.2017.08.034275:C(341-349)Online publication date: 31-Jan-2018
    • (2018)Novel underdetermined blind source separation algorithm based on compressed sensing and K‐SVDTransactions on Emerging Telecommunications Technologies10.1002/ett.342729:9Online publication date: 7-Sep-2018
    • (2017)A Consolidated Perspective on Multimicrophone Speech Enhancement and Source SeparationIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2016.264770225:4(692-730)Online publication date: 1-Apr-2017
    • (2017)Underdetermined Mixing Matrix Estimation Algorithm Based on Single Source PointsCircuits, Systems, and Signal Processing10.1007/s00034-017-0522-936:11(4453-4467)Online publication date: 1-Nov-2017
    • (2017)SSP-Based UBI Algorithms for Uniform Linear ArrayCircuits, Systems, and Signal Processing10.1007/s00034-017-0500-236:10(4077-4096)Online publication date: 1-Oct-2017
    • (2017)Underdetermined Blind Identification for Uniform Linear Array by a New Time---Frequency MethodCircuits, Systems, and Signal Processing10.1007/s00034-016-0292-936:1(99-118)Online publication date: 1-Jan-2017
    • (2016)Supervised single-channel speech enhancement using ratio mask with joint dictionary learningSpeech Communication10.1016/j.specom.2016.06.00182:C(38-52)Online publication date: 1-Sep-2016
    • (2016)Novel mixing matrix estimation approach in underdetermined blind source separationNeurocomputing10.1016/j.neucom.2015.08.008173:P3(623-632)Online publication date: 15-Jan-2016
    • (2015)A robust time-frequency decomposition model for suppression of mixed Gaussian-impulse noise in audio signalsIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2014.237154423:1(69-79)Online publication date: 1-Jan-2015
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