Lpso-wnn Denoising Algorithm for Speech Recognition in High Background Noise

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.