关键词: 语音增强, 解相关, 块处理, 变步长最小均方, 自适应滤波

Abstract: Noise seriously affects the quality of speech signal under complex environment, leading us cannot convey the semantic correctly, so speech enhancement processing becomes very necessary. Traditional technology exist problems as follows: poor adaptability, slow convergence speed when the input signals are heavily correlated. Therefore, an improved algorithm unifies the advantages of Variable Step Size Least Mean Square (VSSLMS) algorithm and de-correlation was proposed to increase the convergence speed by optimizing the step size and update direction of the weight vector in adaptive filter. In order to improve the stability of algorithm implementation in embedded systems, continuous block processing principle was introduced to normalize the weight vector. Simulation tests show that the novel algorithm has fast convergence speed and good performance of tracing time-varying signals. The noise can be removed effectively from speech signal with strong noise, and the speech definition and intelligibility are improved significantly.

Key words: speech enhancement, de-correlation, block processing, Variable Step Size Least Mean Square (VSSLMS), adaptive filter