A new dual forward BSS based RLS (DFRLS) algorithm for speech enhancement
Mohamed Djendi, Rahima Henni, Akila Sayoud · 2016
This paper addresses the speech enhancement problem with adaptive filtering algorithms. We propose a new dual forward blind source separation (FBSS) algorithm based on the use of the recursive least square algorithm to update the cross-filters of the forward structure. This algorithm inherits the good characteristics of the combination between the FBSS and the good properties of the RLS algorithm. In this work, we propose to use the DFRLS algorithm in speech enhancement and acoustic noise reduction application. This proposed algorithm shows good characteristics in comparison with dual forward normalized least mean square (DFNLMS) algorithm is terms of various objective criteria as the segmental signal to noise ratio (SegSNR), the cepstral distance (CD), the system mismatch (SM) and the segmental mean square error (SegMSE).