期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：57
期号：3
出版社：Journal of Theoretical and Applied
摘要：This paper introduces an intelligent evaluation method based on improved PSO-WNN (partiele swarm optimization-wavelet neural network) for speech denoising in high background noise. Firstly, by using Lyapunov stability theory, convergence conditions of a single particle is discussed and based on the result, a new strategy is introduced to improve the performance of the PSO algorithm. Then, the improved PSO algorithm is used to optimize the parameter of the WNN and the LPSO-WNN is introduced. Finally, the trained LPSO-WNN is used to identify and recognition the speech signal in high background noise. Experimental results show that the new method is high efficient and practicable for filtering the high background noise and recognition the speech signal.
关键词：LPSO; WNN; Speech Recognition; High Background Noise; Denoise
