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A new speech enhancement adaptive algorithm based on fullband–subband MSE switching

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Abstract

This paper presents a new fullband–subband switching adaptive speech enhancement algorithm, based on mean square error estimation. The proposed algorithm is able to automatically switch between two adaptive filtering algorithms, i.e. the two-channel fullband normalized least mean square (TC-FNLMS) algorithm and the two-channel subband normalized least mean square (TC-SNLMS), where, the proposed switching mechanism leads to a significant improvement in the convergence speed performance of the proposed algorithm. To confirm the efficiency and the good performances of the proposed algorithm in comparison with the fullband and subband versions of the two channel NLMS algorithm, several experiments were carried out in terms of the segmental signal-to-noise-ratio (SegSNR), segmental mean square error (SegMSE), system mismatch (SM) and cepstral distance (CD).

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Authors and Affiliations

  1. Signal Processing and Image Laboratory (LATSI), University of Blida 1, Route de Soumaa, B.P. 270, Blida, 09000, Algeria

    Akila Sayoud, Mohamed Djendi & Abderrezak Guessoum

Authors
  1. Akila Sayoud
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  2. Mohamed Djendi
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  3. Abderrezak Guessoum
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Correspondence to Mohamed Djendi.

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Sayoud, A., Djendi, M. & Guessoum, A. A new speech enhancement adaptive algorithm based on fullband–subband MSE switching. Int J Speech Technol 22, 993–1005 (2019). https://doi.org/10.1007/s10772-019-09651-4

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  • DOI: https://doi.org/10.1007/s10772-019-09651-4

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