skip to main content
10.1145/3234698.3234722acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicemisConference Proceedingsconference-collections
research-article

A Two-Sensor Fast Adaptive Algorithm for Blind Speech Enhancement

Published: 19 June 2018 Publication 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 presents the enhancement of speech signals in a noisy environment by using a Two-Sensor Fast Normalized Least Mean Square adaptive algorithm combined with the backward blind source separation structure. A comparative study with other competitive algorithms shows the superiority of the proposed algorithm in terms of various objective criteria such as the segmental signal to noise ratio (SegSNR), the cepstral distance (CD), the system mismatch (SM) and the segmental mean square error (SegMSE).

References

[1]
A.H Sayed, "Fundamentals of adaptive filtring," Wiley, 2003.
[2]
A. Benallal, A. Benkrid, "A simplified FTF-type algorithm for adaptive filtering". Signal processing 2007; 87(5):904--917.
[3]
B. Widrow, J.R. Glover, J.M. Mccool, J. Kaunitz, C.S. Williams, R.H. Hearn, J.R.Zeidler, E. Dong, R.C. Goodlin, "Adaptive noise cancelling: principles and applications", Proc. of the IEEE 63 (December (12)) (1975), 1962--1716.
[4]
A. Benallal, M. Arezki, "A fast convergence normalized least-mean-squars type algorithm for adaptive filtring ", international journal of adaptive control and processing, Int.J. control signal process, 2013.
[5]
N.H. Charkani, "Auto-adaptive separation of convolutive mixtures. Applications to hand-free telephony in cars, Ph.D dissertation (in French), National Pollytechnique of Grenoble, France, 1996.
[6]
M. Djendi, R. Bendoumia, "A new efficient two-channel backward algorithm for speech intelligibility enhancement: a subband approach". Appl Acoust2014;76:209--22.
[7]
M. Djendi, P. Scalart, A. Gilloire, "Noise cancellation using two closely spaced microphones: experimental study with a specific model and two adaptive algorithms". In: Proc. IEEE.ICASSP, May 2006. vol.3, pp.744--747.
[8]
M. Djendi, R. Henni, A. Sayoud, "A New dual forward BSS based RLS algorithm for speech enhancement". International Conference on Engineering and MIS, ICEMIS 2016, Agadir, Morooco 2016

Cited By

View all
  • (2020)Efficient subband fast adaptive algorithm based-backward blind source separation for speech intelligibility enhancementInternational Journal of Speech Technology10.1007/s10772-020-09715-w23:2(471-479)Online publication date: 1-Jun-2020

Recommendations

Comments

Information & Contributors

Information

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
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 for this article.

Check for updates

Author Tags

  1. Adaptive filtering
  2. BBSS structure
  3. FNLMS
  4. Speech enhancement

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICEMIS '18

Acceptance Rates

ICEMIS '18 Paper Acceptance Rate 73 of 200 submissions, 37%;
Overall Acceptance Rate 215 of 605 submissions, 36%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 07 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2020)Efficient subband fast adaptive algorithm based-backward blind source separation for speech intelligibility enhancementInternational Journal of Speech Technology10.1007/s10772-020-09715-w23:2(471-479)Online publication date: 1-Jun-2020

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media