Abstract: In order to solve the residual background noise and the musical noise resulted by the existing speech enhancement algorithm for hearing aids, a speech enhancement algorithm based on noise estimation of binary masking is proposed in this paper. The estimated background noise and initial enhanced speech are obtained by using the minima-controlled recursive averaging algorithm. The estimated noise and the initial enhanced speech are processed by gammatone filter and inner cells model and time-frequency representation is obtained. Binary masking of noisy is calculated. The binary masking is used to synthesize enhanced speech by utilizing human auditory masking in time-frequency domain. Experimental results show that the proposed algorithm is compared with the MCRA algorithm, Speech Intelligibility Index（SII）, Perceptual Evaluation of Speech Quality（PESQ） and SNR are improved.

Key words: speech enhancement, hearing aids, noise estimate, binary masking

摘要： 针对现有的助听器语音增强算法在非平稳噪声环境下，残留大量背景噪声的同时还引入了“音乐噪声”，致使增强语音可懂度和信噪比不理想等问题。提出了一种基于噪声估计的二值掩蔽语音增强算法，该算法利用人耳听觉感知理论，结合人耳的听觉特性和耳蜗的工作机理。采用最小值控制递归平均（Minima-Controlled Recursive Averaging，MCRA）算法获得估计噪声和初步增强语音；将估计噪声和初步增强语音分别通过可以模拟人工耳蜗模型的gammatone滤波器组进行滤波处理，得到各自的时频表示形式；利用人耳的听觉掩蔽特性，计算含噪语音在时频域的二值掩蔽；利用二值掩蔽得到增强语音。实验结果表明：该算法很大程度上去除了谱减法引入的“音乐噪声”，与基于MCRA谱减法相比，增强语音的语言可懂度指数（Speech Intelligibility Index，SII）、主观语音质量评估（Perceptual Evaluation of Speech Quality，PESQ）和信噪比（Signal to Noise Ratio，SNR）都得到了提高。

关键词: 语音增强, 助听器, 噪声估计, 二值掩蔽