中文摘要：

针对语音增强算法中传统的小波阈值法的局限性，提出一种基于可调Q-因子小波变换和清浊音分离的语音增强算法。首先用过零率和短时能量法判别清音和浊音；然后在可调Q-因子小波变换下，对清、浊音采用不同的阈值处理，在不同尺度上，分别结合系数能量和噪声方差得到的阈值作为清音和浊音的阈值确定准则；再利用改进的阈值函数分别处理清音和浊音的小波系数，估计出不含噪声的系数；最后进行小波逆变换，得到抑制了噪声的语音信号。对含有高斯白噪声和有色噪声的语音进行仿真实验，结果表明：与目前许多经典的去噪方法相比，该方法在去噪效果和提高语音可懂度方面均有一定的改善。

英文摘要：

Aiming at the limitations of methods on speech enhancement by traditional threshold methods in wavelet domain, this paper proposed a new speech enhancement algorithm based on the tunable Q-factor wavelet transform and separation of voiced signal and unvoiced signal.Firstly,it separated voiced signal and unvoiced signal with zero-crossing ratio and short-time energy.The adaptive threshold values combined the energy of coefficients and the variance of noise in different scales,re-spectively.Then it applied the improved Donoho threshold value and threshold function to process wavelet coefficients of voiced signal and unvoiced signal,and estimated the original coefficients from noisy coefficients.Lastly,it used the inverse transform to obtain the original speech signal which the noise was removed.Comparing with the other current classical algo-rithms,experimental results show that the modified algorithm improves the effect of de-noising and speech intelligibility in white Gaussian noise and colored noise background.