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

10.10.2018

A new robust forward BSS adaptive algorithm based on automatic voice activity detector for speech quality enhancement

verfasst von: Meriem Zoulikha, Mohamed Djendi

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

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Abstract

This paper presents a new adaptive blind source separation (BSS) algorithm for acoustic noise reduction and speech enhancement applications in a car framework. The forward BSS structure is often used to separate speech from noise and enhances the speech signal at the output processing. The drawback of most speech enhancement methods that are based on BSS structures is the use of a manual voice activity detection (VAD) system to control the source separation process. In this work, we propose a new algorithm based on the forward BSS structure and an automatic VAD (AVAD) system. The new AVAD system uses an adaptive approach based on a modified normalized least mean square (NLMS) adaptive algorithm to get a new speech enhancement algorithm. This proposed algorithm allows to: (i) reduce the computational complexity of previous techniques based on AVAD system; (ii) enhance the quality of the output speech signal. We have carried out intensive experiments on the proposed algorithm and others state of the art algorithms that use VAD or AVAD systems. In this paper, we show the efficiency of the proposed algorithm in terms of objective and subjective criteria.
Vorheriger Artikel Correction to: Revisiting distinctive phonetic features from applied computing perspective: unifying views and analyzing modern Arabic speech varieties
Nächster Artikel Digital speech watermarking to enhance the security using speech as a biometric for person authentication

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Metadaten
Titel
A new robust forward BSS adaptive algorithm based on automatic voice activity detector for speech quality enhancement
verfasst von
Meriem Zoulikha
Mohamed Djendi
Publikationsdatum
10.10.2018
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/s10772-018-9555-0

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