skip to main content
10.1145/3234698.3234715acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicemisConference Proceedingsconference-collections
research-article

A Dual Backward Adaptive Algorithm for Speech Enhancement and Acoustic Noise Reduction

Authors Info & Claims
Published:19 June 2018Publication History

Editorial Notes

NOTICE OF CONCERN: ACM has received evidence that casts doubt on the integrity of the peer review process for the ICEMIS 2018 Conference. As a result, ACM is issuing a Notice of Concern for all papers published and strongly suggests that the papers from this Conference not be cited in the literature until ACM's investigation has concluded and final decisions have been made regarding the integrity of the peer review process for this Conference.

ABSTRACT

This paper deals with the problem of noise reduction for hands-free communications when two microphones are in use. Recently, forward-and-backward blind source separation (BSS) structures have been suggested to solve acoustic noise reduction and speech enhancement problems. Therefore, we propose a new algorithm that is based on the combination between the dual backward (BSS) structure and the Simplified Fast Transversal Filter (SFTF) algorithm. The obtained results which are expressed in terms of several objective criteria prove and confirm the superiority and the good performances of the proposed dual backward blind SFTF (DBSFTF) in comparison with the classical dual backward normalized least mean square (DBNLMS) algorithm.

References

  1. Philipos Loizou C. "Speech enhancement: theory and practice". 2nd Edition. CRC press, Taylor & Francis Group; 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Van Compernolle D, Leuven KU. "Switching adaptive filters for enhancing noisy and reverberant speech from microphone array recordings". In: Proceedings of the IEEE International conference on acoustics, speech and signal processing;Google ScholarGoogle Scholar
  3. Sugiyama, A., Swamy, M.N.S, Plotkin, E.I., 1989. "A fast convergence algorithm for adaptive FIR filters". In: Proc. IEEE ICASSP, vol. 2, pp. 892--895.Google ScholarGoogle ScholarCross RefCross Ref
  4. M. Djendi, R. Bendoumia. "A new efficient two-channel backward algorithm for speech intelligibility enhancement: a subband approach". Appl Acoust 2014;76:209--22.Google ScholarGoogle ScholarCross RefCross Ref
  5. A.H. Sayed. "Fundamentals of Adaptive Filtering". Wiley, New York, 2003.Google ScholarGoogle Scholar
  6. M. Djendi, A. Sayoud, R. Henni. "A Dual Forward BSS Based RLS (DFRLS) algorithm for Speech Enhancement and Acoustic Noise Reduction", International Conference on Engineering and MIS, ICEMIS'2016, At Agadir, Morocco.Google ScholarGoogle Scholar
  7. Al-Kindi, M.J., Dunlop, J. "Improved adaptive noise cancellation in the presence of signal leakage on the noise reference channel". Signal Processing 17 (3), 241--250, 1989.Google ScholarGoogle ScholarCross RefCross Ref
  8. Van Gerven S, Van Compernolle D. "Feed forward and feedback in symmetric adaptive noise canceller: stability analysis in a simplified case". In: European signal processing conf. Brussels. Belgium. August 1992. p. 1081--4.Google ScholarGoogle Scholar
  9. M. Djendi, P. Scalart, A. Gilloire. "Analysis of two-sensor forward BSS structure with post-filters in the presence of coherent and incoherent noise". Speech Commun 2013;55(10):975--87, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. A. Benallal, M. Arezki. "A fast convergence normalized least-mean-square type algorithm for adaptive filtering", International Journal of Adaptive Control and Signal Processing 2013,Google ScholarGoogle Scholar
  11. M. Djendi, A. Gilloire, P. Scalart. "Noise cancellation using two closely spaced microphones: experimental study with a specific model and two adaptive algorithms". In: proceedings of the IEEE ASSP International Conference, May 2006, vol. 3, pp. 744--74.Google ScholarGoogle ScholarCross RefCross Ref
  12. M. Djendi, M. Zoulikha. "New automatic forward and backward blind sources separation algorithms for noise reduction and speech enhancement". Computers and Electrical Engineering, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Hu Y, Loizou PC. "Subjective comparison and evaluation of speech enhancement algorithms". Speech Commun 2007;49(7):588--601. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. J. Kocinski, AP. "Sek Speech intelligibility in various spatial configurations of background noise". Arch Acoust 2005, 30(2):173--91.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    ICEMIS '18: Proceedings of the Fourth International Conference on Engineering & MIS 2018
    June 2018
    452 pages
    ISBN:9781450363921
    DOI:10.1145/3234698

    Copyright © 2018 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 19 June 2018

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    ICEMIS '18 Paper Acceptance Rate73of200submissions,37%Overall Acceptance Rate215of605submissions,36%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader