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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 4/2018

13.08.2018

A new efficient backward BSS crosstalk-resistant algorithm for automatic blind speech quality enhancement

verfasst von: Mohamed Djendi, Meriem Zoulikha

Erschienen in: International Journal of Speech Technology | Ausgabe 4/2018

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Abstract

In last 10 years, several noise reduction (NR) algorithms have been proposed to be combined with the blind source separation techniques to separate speech and noise signals from blind noisy observations. More often, techniques use voice activity detector (VAD) systems for the optimal solution. In this paper, we propose a new backward blind source separation (BBSS) structure that uses the input correlation properties to provide: (i) high convergence rates and good tracking capabilities, since the acoustic environments imply long and time-variant noise paths, and (ii) low misalignment and robustness against different noise type variations and double-talk. The proposed algorithm has an automatic behavior to enhance noisy speech signals, and do not need any VAD systems to separate speech and noise signals. The obtained results in terms of several objective criteria show the good performance properties of the proposed algorithm in comparison with state-of-the-art algorithms.
Vorheriger Artikel Mel scaled M-band wavelet filter bank for speech recognition
Nächster Artikel Large scale data based audio scene classification

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Metadaten
Titel
A new efficient backward BSS crosstalk-resistant algorithm for automatic blind speech quality enhancement
verfasst von
Mohamed Djendi
Meriem Zoulikha
Publikationsdatum
13.08.2018
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 4/2018
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-018-9544-3

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