This paper proposes an improved method of solving the permutation problem inherent in frequency-domain of convolutive blind source separation (BSS). It combines a novel inter-frequency dependence measure: the power ratio of separated signals, and a simple but effective bin-wise permutation alignment scheme. The proposed method is easy to implement and surpasses the conventional ones. Simulations have shown that it can provide an almost ideal solution of the permutation problem for a case where two or three sources were mixed in a room with a reverberation time of 130 ms.

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.