Blind speech enhancement and acoustic noise reduction by SFTF adaptive algorithm

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 prop...

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Vydáno v:2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B) s. 1 - 4
Hlavní autoři: Rahima, Henni, Djebari, Mustapha, Mohamed, Djendi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2017
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Abstract 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.
AbstractList 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.
Author Djebari, Mustapha
Rahima, Henni
Mohamed, Djendi
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  surname: Rahima
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  organization: Detection, Information and Communication (DIC) laboratory. University of Blida 1, Route de Soumaa, B.P. 270, Blida 09000, Algeria
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  givenname: Mustapha
  surname: Djebari
  fullname: Djebari, Mustapha
  organization: Detection, Information and Communication (DIC) laboratory. University of Blida 1, Route de Soumaa, B.P. 270, Blida 09000, Algeria
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  givenname: Djendi
  surname: Mohamed
  fullname: Mohamed, Djendi
  organization: Laboratory of signal Processing and Imaging (LATSI). University of Blida 1, Route de Soumaa, B.P. 270, Blida 09000, Algeria
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Snippet In this paper, we address the problem of noise reduction and speech enhancement by adaptive filtering algorithms using the forward blind source separation...
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SubjectTerms Adaptive filters
Algorithm design and analysis
Cepstral analysis
FBSS structure
NLMS algorithm
SFTF algorithm
Signal processing algorithms
Signal to noise ratio
Speech
Speech enhancement
Title Blind speech enhancement and acoustic noise reduction by SFTF adaptive algorithm
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