中文摘要：

单通道语音增强中,已有的先验信噪比算法能有效地去除噪声,提升语音增强算法性能;但是由于在噪声功率谱估计不准确,造成噪声功率出现过估和低估的情况,造成了语音失真和保留较多残留噪声。通过倒谱处理能在含噪语音段中抑制语音中的谐频成分和在纯噪声段中避免部分较强的噪声成分误判为语音信号,准确地估计出噪声功率谱,同时语音失真不大。在多种噪声背景下的客观评价指标分析表明,经过倒谱处理后的先验信噪比估计算法能提高先验信噪比算法的估计性能。

英文摘要：

For single-channel speech enhancement systems,the a priori SNR is a key parameter for Wiener-type algorithms. The a priori SNR estimators can reduce the noise efficiently when the noise power spectral density（ NPSD） can be estimated accurately. However,when the NPSD is overestimated /underestimated,the a priori SNR may lead to the speech distortion and the residual noise. To solve this problem,the a priori SNR proposed to estimate based on cepstral processing,which not only can suppress harmonic speech components in the noisy speech segments,but also can reduce strong noise components in noise-only segments. Simulation results show that the proposed algorithm has better performance than the traditional DD and Plapous＇ s two-step algorithms.