An Improved LSA-MMSE Speech Enhancement Approach Based on Auditory Perception

L. Gong, Changxing Chen, Qi Chen, Haoxiang Xu
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引用次数: 1

Abstract

Gain function of traditional enhancement algorithm is to estimate every signal spectral component, therefore, this introduce relatively more speech distortion. To improve the effect of speech enhancement at low signal-to-noise ratio (SNR), this paper proposed a optimal speech enhancement scheme. Based on auditory perception properties, no estimator for noise masked spectrum and classical enhancement estimator for noise unmasked spectrum. Then a speech signal estimator is proposed as a weighted sum of the individual estimator in each state, where the weight is related with noise masked probability. Compared with Viragpsilas method and LSA-MMSE estimator, the proposed estimator can suppress the residual noise effectively while keep smaller speech distortion especially at low SNR.
一种基于听觉感知的改进LSA-MMSE语音增强方法
传统增强算法的增益函数是对每个信号的频谱分量进行估计,因此会引入较多的语音失真。为了提高低信噪比下的语音增强效果,提出了一种优化的语音增强方案。基于听觉感知特性,对噪声掩码谱进行无估计,对噪声去掩码谱进行经典增强估计。然后提出了一个语音信号估计器,作为每个状态下单个估计器的加权和,其中权重与噪声掩盖概率有关。与Viragpsilas方法和LSA-MMSE估计方法相比,该估计方法能够有效抑制残差噪声,在低信噪比下保持较小的语音失真。
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