Dual channel speech enhancement using normalized fractional least mean squares algorithm
In this paper, we propose a novel method, called normalized fractional least mean squares (NFLMS) for dual channel speech enhancement. Here, we use a modified least mean squares algorithm known as fractional LMS, by incorporating the fractional term in weight adaptation equation of the standard least mean squares algorithm. Normalization provides an interesting way to improve standard least mean squares performance. In order to promote the performance of the fractional LMS algorithm, we propose normalized version of fractional least mean squares. Experimental results shows that the proposed method has better performance in dual channel speech enhancement in a sense of mean squares error (MSE) and speech quality improvement than the standard LMS, Normalized LMS, and Fractional LMS algorithms.
2011 19th Iranian Conference on Electrical Engineering