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Multiple sub filter based proportionate filtering for nonlinear acoustic echo cancellation.

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Title: Multiple sub filter based proportionate filtering for nonlinear acoustic echo cancellation.
Authors: Burra, Srikanth1 (AUTHOR) edm19d001@iiitdm.ac.in, Kar, Asutosh1 (AUTHOR) asutoshkar@iiitdm.ac.in, Østergaard, Jan2 (AUTHOR) jo@es.aau.dk
Source: Applied Acoustics. Nov2021, Vol. 182, pN.PAG-N.PAG. 1p.
Subjects: Acoustic filters, Adaptive filters, Signal-to-noise ratio, Algorithms, Spectrograms
Abstract: This paper presents a multiple sub-filter-based improved nonlinear acoustic echo cancellation (NAEC) framework to enhance the echo cancellation performance of the NAEC in the presence of nonlinear distortion. The proposed algorithm uses a novel combination of adaptive multiple sub-filter approach and proportionate filtering to enhance the convergence rate of the existing proportionate functional link-based NAEC algorithm by reducing the adaption time needed for updating the coefficients of the adaptive filter. In addition to that, the convergence and the steady-state analysis of the proposed algorithm are presented. The proposed NAEC framework is subjected to speech signal input corrupted with both white as well as colored noise as background noise and the colored noise input at low-to–high SNR conditions for a comprehensive analysis of the echo cancellation performance. The experimental results comprising of the echo return loss enhancement, spectrograms, and the perceptual evaluation of speech quality demonstrate the improvements brought by the proposed algorithm. At all signal-to-noise ratio conditions, the proposed algorithm has shown a 4 dB improvement in mean echo return loss enhancement compared to the existing algorithms validating the improvement in the proposed NAEC scheme's performance. [ABSTRACT FROM AUTHOR]
Copyright of Applied Acoustics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
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  Data: Multiple sub filter based proportionate filtering for nonlinear acoustic echo cancellation.
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  Data: <searchLink fieldCode="AR" term="%22Burra%2C+Srikanth%22">Burra, Srikanth</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> edm19d001@iiitdm.ac.in</i><br /><searchLink fieldCode="AR" term="%22Kar%2C+Asutosh%22">Kar, Asutosh</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> asutoshkar@iiitdm.ac.in</i><br /><searchLink fieldCode="AR" term="%22Østergaard%2C+Jan%22">Østergaard, Jan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jo@es.aau.dk</i>
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  Data: <searchLink fieldCode="JN" term="%22Applied+Acoustics%22">Applied Acoustics</searchLink>. Nov2021, Vol. 182, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Acoustic+filters%22">Acoustic filters</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+filters%22">Adaptive filters</searchLink><br /><searchLink fieldCode="DE" term="%22Signal-to-noise+ratio%22">Signal-to-noise ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Spectrograms%22">Spectrograms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper presents a multiple sub-filter-based improved nonlinear acoustic echo cancellation (NAEC) framework to enhance the echo cancellation performance of the NAEC in the presence of nonlinear distortion. The proposed algorithm uses a novel combination of adaptive multiple sub-filter approach and proportionate filtering to enhance the convergence rate of the existing proportionate functional link-based NAEC algorithm by reducing the adaption time needed for updating the coefficients of the adaptive filter. In addition to that, the convergence and the steady-state analysis of the proposed algorithm are presented. The proposed NAEC framework is subjected to speech signal input corrupted with both white as well as colored noise as background noise and the colored noise input at low-to–high SNR conditions for a comprehensive analysis of the echo cancellation performance. The experimental results comprising of the echo return loss enhancement, spectrograms, and the perceptual evaluation of speech quality demonstrate the improvements brought by the proposed algorithm. At all signal-to-noise ratio conditions, the proposed algorithm has shown a 4 dB improvement in mean echo return loss enhancement compared to the existing algorithms validating the improvement in the proposed NAEC scheme's performance. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Acoustics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.apacoust.2021.108215
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Acoustic filters
        Type: general
      – SubjectFull: Adaptive filters
        Type: general
      – SubjectFull: Signal-to-noise ratio
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Spectrograms
        Type: general
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      – TitleFull: Multiple sub filter based proportionate filtering for nonlinear acoustic echo cancellation.
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            NameFull: Burra, Srikanth
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            NameFull: Kar, Asutosh
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            NameFull: Østergaard, Jan
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            – D: 01
              M: 11
              Text: Nov2021
              Type: published
              Y: 2021
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              Value: 182
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