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A dual fast NLMS adaptive filtering algorithm for blind speech quality enhancement

APPLIED ACOUSTICS 2018年第Jun.期135卷 101-110页

作者： Sayoud, Akila Djendi, Mohamed Medahi, Soumia Guessoum, Abderrezak Univ Blida 1 Signal Proc & Image Lab LATSI Route SoumaaBP 270 Blida 09000 Algeria

This paper addresses the problem of acoustic noise reduction and speech enhancement in new telecommunications systems by adaptive filtering algorithms. Recently, a particular attention has been made to the blind source separation (BSS) approach applied for the separation of speech and noise components. The BSS application has inherits the good properties of the adaptive filtering algorithm to give more intelligible enhanced speech signal in term of quality. In this paper, we propose a new dual forward BSS algorithm that is based on signal prediction to give an automatic algorithm with a very fine behavior at the output. This algorithm is called the dual fast normalized least mean square (DFNLMS) algorithm. This algorithm has been tested in various noisy conditions and has shown its superiority in terms of the following objective criteria: cepstral distance (CD), segmental signal-to-noise-ratio (SegSNR), segmental mean square error (SegMSE), and system mismatch (SM). A comparison with other competitive and state-of-the-art algorithms is also presented in this paper.

关键词： fbss structure Noise reduction SNR factor Speech enhancement FNLMS

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

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INTERNATIONAL JOURNAL OF SPEECH TECHNOLOGY 2019年第2期22卷 391-406页

作者： Djendi, Mohamed Sayoud, Akila Univ Blida 1 Signal Proc & Image Lab LATSI Route SoumaaBP 270 Blida 09000 Algeria

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.

关键词： fbss structure Subband adaptive filtering DFNLMS Noise reduction

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Blind Speech Enhancement and Acoustic Noise Reduction by SFTF Adaptive Algorithm 5

Blind Speech Enhancement and Acoustic Noise Reduction by SFT...

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5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)

作者： Rahima, Henni Djebari, Mustapha Mohamed, Djendi Univ Blida 1 Detect Informat & Commun DIC Lab Blida 09000 Algeria Univ Blida 1 Lab Signal Proc & Imaging LATSI Route SoumaaBP 270 Blida 09000 Algeria

ISBN: (纸本)9781538606865

In this paper, we address the problem of noise reduction and speech enhancement by adaptive filtering algorithms using the forward blind source separation structure (fbss), which is often combined with adaptive algorithms to efficiently cancel the acoustic noise at the output. In this paper, we propose to combine the fbss with the Simplified Fast Transversal Filter (SFTF) algorithm, where the adaptation gain is obtained only from the forward prediction. The performances of the proposed SFTF algorithm are compared with the Normalized Least Mean Square (NLMS) algorithm in different noisy conditions. This comparison is evaluated in terms of Cepstral Distance (CD), the System Mismatch (SM) and the Segmental Signal to Noise Ratio (SegSNR) criteria.

关键词： Speech enhancement SFTF algorithm fbss structure NLMS algorithm

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A Two-Channel Fast NLMS Algorithm for Speech Enhancement and Acoustic Noise Reduction 5

A Two-Channel Fast NLMS Algorithm for Speech Enhancement and...

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5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)

作者： Sayoud, Akila Djendi, Mohamed Guessoum, Abderrezak Univ Blida 1 Signal Proc & Image Lab LATSI Route Soumaa Bp 270 Blida 09000 Algeria

ISBN: (纸本)9781538606865

this paper addresses the problem of acoustic noise reduction and speech enhancement in new telecommunication systems by adaptive filtering algorithms. We propose a new two-channel forward BSS algorithm based on signal prediction to give an automatic algorithm with a very nice behavior at the output. This algorithm is called the two-channel fast normalized least mean square (TCFNLMS) algorithm. This new algorithm shows superiority in comparison with classical two-channel NIMS in terms of the following objective criteria: the segmental signal to noise ratio (SegSNR), the cepstral distance (CD), the system mismatch (SM) and the segmental mean square error (SegMSE).

关键词： fbss structure Noise reduction SNR factor FNLMS

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