Noise Cancellation In Speech Signal Processing Using Adaptive Algorithm

Abstract

Speech has always been one of the most important carriers of information for people it becomes a challenge to maintain its high quality. In many application of noise cancellation, the changes in signal characteristics could be quite fast. This requ ires the utilization of adaptive algorithms, which converge rapidly. Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) adaptive filters have been used in a wide range of signal processing application because of its simplicity in computation and implementation. The Recursive Least Squares (RLS) algorithm has established itself as the "ultimate" adaptive filtering algorithm in the sense that it is the adaptive filter exhibiting the best convergence behavior. Unfortunately, practical implementations o f the algorithm are often associated with high computational complexity and/or poor numerical properties. Recently adaptive filteri ng was presented, have a nice tradeoff between complexity and the convergence speed. This paper describes a new approach for n oise cancellation in speech signal using the new adaptive filtering algorithm named affine projection algorithm for attenuating no ise in speech signals. The simulation results demonstrate the good performance of the new algorithm in attenuating the noise.