Optimizing Speech Enhancement Based on Noise Masked Probability
基于噪声被掩蔽概率的优化语音增强方法

An optimal approach for enhancing a speech signal degraded by uncorrelated stationary additive noise, which exploits auditory perception properties, is proposed. The speech spectra estimate is performed in two cases: noisy speech spectra for noise masked and classical estimate for noise unmasked. Taking account into the uncertainty of the noise presence, the enhanced speech signal spectra are obtained by a weighted sum of these two estimates, where the weights are given by the noise masked probability. The performance of the proposed speech enhancement approach has been evaluated with speech distortion and informal listening tests. Comparing with Azirani's method and classical estimator, results show that a better compromise between reducing speech distortion and reinforcing noise suppression has been made, speech distortion has been decreased apparently, musical noise has been suppressed and speech articulation has been improved.