A new dual subband fast NLMS adaptive filtering algorithm for blind speech quality enhancement and acoustic noise reduction

This paper discusses the problem of acoustic noise reduction and speech enhancement through the forward blind source separation structure. Recently we have proposed a new combination between the forward blind source separation structure and the fast normalized least mean square algorithm that provid...

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Bibliographic Details
Published in:International journal of speech technology 2019-06, Vol.22 (2), p.391-406
Main Authors: Djendi, Mohamed, Sayoud, Akila
Format: Article
Language:English
Subjects:
Acoustic noise
Acoustics
Adaptive algorithms
Adaptive filters
Algorithms
Artificial Intelligence
Engineering
Mean square values
Noise
Noise reduction
Separation
Signal processing
Signal,Image and Speech Processing
Social Sciences
Source separation
Speech enhancement
Speech processing
Terminology
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Summary:This paper discusses the problem of acoustic noise reduction and speech enhancement through the forward blind source separation structure. Recently we have proposed a new combination between the forward blind source separation structure and the fast normalized least mean square algorithm that provides an efficient dual algorithm for noise reduction and speech enhancement applications. In this paper we propose a new subband implementation of this recent dual algorithm, this last allows improving the speed convergence behavior of the previous proposed algorithm in its fullband form. The performance of the proposed dual subband algorithm is compared with its fullband version of the dual fast normalized least mean square algorithm and the classical fullband dual normalized least mean square algorithm, and the two channel subband forward algorithm in terms of several objective criteria. The obtained results show the good performances of the proposed dual subband algorithm.
ISSN:1381-2416
1572-8110
DOI:10.1007/s10772-019-09614-9