A Dual Backward Adaptive Algorithm for Speech Enhancement and Acoustic Noise Reduction

Henni, Rahima; Djendi, Mohamed; Djebari, Mustapha

doi:10.1145/3234698.3234715

Cited by 3 publications

(1 citation statement)

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“…Based on the usage of the recursive least square algorithm [8], forward blind structure is to update the cross-filters. Feed forward and feedback structures are the types of blind source separation [9] to resolve speech enhancement issues. A DFNLMS algorithm [10] aimed at speech quality improvement.…”

Section: Introductionmentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Nidhyananthan¹,

Priya²,

Kumari³

2019

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Speech enhancement objective is to improve the noisy speech signals for human perception. The intention of speech enhancement algorithm is to improve the performance of the communication, when the signal is occluded by noise. The quality and intelligibility of speech is reduced because of the presence of background noise. There are various adaptive filtering algorithms for speech enhancement. The existing least mean square and normalised least mean square algorithms have the problem of choosing the step size that guarantees the stability of the algorithm. To overcome this problem, we focus on speech enhancement by amended adaptive filtering. The proposed algorithm follows blind source separation strategy using adaptive filtering. Comparison of existing adaptive filtering algorithms with proposed algorithm justifies the amendment incorporated in this paper. Taking the objective criteria into account the algorithms has been tested for segmental signal to noise ratio (SegSNR), segmental mean square error (SegMSE), signal to noise ratio and mean square error. The proposed algorithm can be used for hand-free cell phone, hearing aids and teleconferencing systems.

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Section: Introductionmentioning

confidence: 99%