A New Algorithm for Speech Enhancement Using Wavelet Packet Transform Based on Auditory Model

Abstract

Human auditory has non-linear characteristics, while wavelet packet transform (WPT) has flexible analysis ability to time-frequency property so that it is more compatible to simulate the human auditory model. In this paper, human auditory model is analyzed, after which a new algorithm for speech enhancement using node-threshold wavelet packet transform based on bark-scaled decomposition is established, multi-resolution singular spectral entropy method is applied to estimate the node noise, and uses soft threshold to deal wavelet transform coefficient. The experiments show that this algorithm is valid on various noise conditions, especially for color noise and non-stationary noise conditions.