Wavelet denoising method based on improved threshold function
Kezhong Sun, Yingchun Lu, Liansheng Huang, Xiaojiao Chen, Xiuqing Zhang, Shiying He · 2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) · 2022
Voice signal is disturbed by environmental noise during recording, which reduces the clarity of voice signal and affects the acquisition of useful signals. The wavelet threshold de noising method is widely used in the field of signal de noising. However, the hard/soft thresholding function in traditional wavelet transform has some problems such as discontinuity and fixed deviation when filtering. Therefore, an improved wavelet thresholding function method is proposed and applied in speech signal denoising. Through theoretical analysis and simulation, the results show that the improved wavelet threshold denoising algorithm can not only improve the signal-to-noise ratio (SNR) of the voice signal, but also largely avoid the distortion of the voice signal.