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Nonlinear acoustic echo cancellation with kernelized adaptive filters.

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Title: Nonlinear acoustic echo cancellation with kernelized adaptive filters.
Authors: Sankar, Sanjana1 (AUTHOR) esd15i020@iiitdm.ac.in, Kar, Asutosh1 (AUTHOR) asutoshkar@iiitdm.ac.in, Burra, Srikanth1 (AUTHOR) edm19d001@iiitdm.ac.in, Swamy, M.N.S.2 (AUTHOR) swamy@ece.concordia.ca, Mladenovic, Vladimir3 (AUTHOR) vladimir.mladenovic@ftn.kg.ac.rs
Source: Applied Acoustics. Sep2020, Vol. 166, pN.PAG-N.PAG. 1p.
Subjects: Echo, Adaptive filters, Signal-to-noise ratio, Least squares, Oral communication, Communicative disorders, Nonlinear acoustics
Abstract: A well-known problem in speech communication is the occurrence of acoustic echo in hands-free telephony. There are several classical adaptive filters that have been used as a stand alone approach for linear acoustic echo cancellation(AEC). A common assumption in most AEC techniques is that the echo path is linear. However, in real scenarios, owing to distortions introduced by other acoustic artefacts in handheld devices, the echo path is nonlinear. Therefore, there is a need to employ a nonlinear echo canceller. In this paper, a kernel expansion on a family of adaptive filtering algorithms based on least mean square filter is proposed. Kernel methods help model the nonlinear echo path and attain global minimum easily by finding the optimal set of filter weights. The simulations are carried out for speech signal with and without noise under different signal-to-noise ratio values. The results show that the proposed method achieves a significant improvement in a nonlinear acoustic echo cancellation environment in terms of echo return loss enhancement. [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.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 143417871
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PubTypeId: academicJournal
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  Data: Nonlinear acoustic echo cancellation with kernelized adaptive filters.
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  Data: <searchLink fieldCode="AR" term="%22Sankar%2C+Sanjana%22">Sankar, Sanjana</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> esd15i020@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="%22Burra%2C+Srikanth%22">Burra, Srikanth</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> edm19d001@iiitdm.ac.in</i><br /><searchLink fieldCode="AR" term="%22Swamy%2C+M%2EN%2ES%2E%22">Swamy, M.N.S.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> swamy@ece.concordia.ca</i><br /><searchLink fieldCode="AR" term="%22Mladenovic%2C+Vladimir%22">Mladenovic, Vladimir</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> vladimir.mladenovic@ftn.kg.ac.rs</i>
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  Data: <searchLink fieldCode="DE" term="%22Echo%22">Echo</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="%22Least+squares%22">Least squares</searchLink><br /><searchLink fieldCode="DE" term="%22Oral+communication%22">Oral communication</searchLink><br /><searchLink fieldCode="DE" term="%22Communicative+disorders%22">Communicative disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+acoustics%22">Nonlinear acoustics</searchLink>
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  Data: A well-known problem in speech communication is the occurrence of acoustic echo in hands-free telephony. There are several classical adaptive filters that have been used as a stand alone approach for linear acoustic echo cancellation(AEC). A common assumption in most AEC techniques is that the echo path is linear. However, in real scenarios, owing to distortions introduced by other acoustic artefacts in handheld devices, the echo path is nonlinear. Therefore, there is a need to employ a nonlinear echo canceller. In this paper, a kernel expansion on a family of adaptive filtering algorithms based on least mean square filter is proposed. Kernel methods help model the nonlinear echo path and attain global minimum easily by finding the optimal set of filter weights. The simulations are carried out for speech signal with and without noise under different signal-to-noise ratio values. The results show that the proposed method achieves a significant improvement in a nonlinear acoustic echo cancellation environment in terms of echo return loss enhancement. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  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.2020.107329
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      – Code: eng
        Text: English
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        PageCount: 1
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      – SubjectFull: Echo
        Type: general
      – SubjectFull: Adaptive filters
        Type: general
      – SubjectFull: Signal-to-noise ratio
        Type: general
      – SubjectFull: Least squares
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      – SubjectFull: Oral communication
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      – SubjectFull: Communicative disorders
        Type: general
      – SubjectFull: Nonlinear acoustics
        Type: general
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      – TitleFull: Nonlinear acoustic echo cancellation with kernelized adaptive filters.
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            NameFull: Sankar, Sanjana
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            NameFull: Kar, Asutosh
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            NameFull: Mladenovic, Vladimir
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            – D: 01
              M: 09
              Text: Sep2020
              Type: published
              Y: 2020
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              Value: 166
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