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

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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.

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Authors and Affiliations

  1. Signal Processing and Image Laboratory (LATSI), University of Blida 1, Route of Soumaa, B.P. 270, 09000, Blida, Algeria

    Meriem Zoulikha & Mohamed Djendi

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  1. Meriem Zoulikha
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  2. Mohamed Djendi
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Correspondence to Mohamed Djendi.

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Zoulikha, M., Djendi, M. A new robust forward BSS adaptive algorithm based on automatic voice activity detector for speech quality enhancement. Int J Speech Technol 21, 1007–1020 (2018). https://doi.org/10.1007/s10772-018-9555-0

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