双通道能量差后滤波语音增强算法统计分析和改进

摘要

双通道能量差后滤波语音增强算法在语音通信系统的噪声抑制技术中有较好的应用前景，然而其理论性能和局限性还未得到充分研究。为此，本文采用统计分析方法研究了双通道能量差后滤波语音增强算法的性能，分析了相干性、平滑因子及噪声估计误差对算法的影响。理论和仿真结果表明，噪声估计误差和平滑因子严重影响该算法的降噪性能。依据此分析结果，本文提出一种基于非平稳噪声估计和功率谱自适应平滑的双通道能量差后滤波算法。测试结果表明，本文提出的算法在不增加语音失真的前提下，能更有效地抑制非平稳噪声，段信噪比提高（SegSNRI）和语音质量感知评估（PESQ）等客观评价指标都表明本文的算法优于其他几种经典的后滤波算法。%The dual-channel power-level-difference-based (PLD-based)post-filter estimator has a bright prospect of ap-plication in the noise reduction technology of voice communication systems,while its theoretical performance and limits are still not well studied.For this purpose,this paper studies the statistical properties of the PLD-based post-filter estimator. By this study,we reveal the impacts of the three parameters including the coherence,the smoothing factor and the noise es-timation error on the performance of the PLD-based post-filter estimator.Both theoretical results and simulation results indi-cate that the noise estimation error and the smoothing factor have significant impacts on the noise reduction performance of the traditional PLD-based post-filter estimator.According to these analysis results,a novel PLD-based post-filter estimator is proposed,which is based on the non-stationary noise estimation method and the adaptive smoothing power spectral densi-ty (PSD)estimation.Experimental results show that the proposed post-filter estimator could suppress more non-stationary noise components without introducing audible speech distortion.Moreover,the proposed algorithm performs better than oth-er state-of-the-art dual-channel post-filter estimators in terms of both the segmental signal-to-noise-ratio improvement (Seg-SNRI)and the perceptual evaluation of speech quality (PESQ)score.