Application of denoising algorithm based on LPSO-WNN in speech recognition

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, the convergence conditions for single particle in PSO algorithm are discussed and a new strategy based on the result is introduced to improve the performance of PSO algorithm. Then, LPSO-WNN is introduced, in which the improved PSO algorithm is used to optimize the parameters of WNN. 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.