摘要
针对封闭环境下的混响对智能语音处理系统性能的影响,论文提出了一种麦克风阵列语音去混响方法。考虑到阵列接收信号所构建的协方差矩阵存在部分数值为零,进而造成输出语音信号失真的情况,论文给出基于两个通道语音信号功率谱的相干扩散功率比(CDR)来实现协方差初始化,采用递归平均得到阵列接收信号协方差矩阵的估计值,进行通过多通道线性预测来优化MCLP的去混响方法。实验结果表明,通过不同混响条件下不同方法的比较,论文提出的去混响算法均取得了较好的去混响效果。
In order to avoid the impact of reverberation in enclosed environments on the intelligent speech processing system,an adaptive speech dereverbration method was proposed in this thesis.Given that some values of the covariance matrix constructed by the speech signal on microphone array might be zero,which may cause distortion of the output speech signal.The speech dereverbration using multi-channel linear prediction(MCLP)were adopted in the thesis,based on double-channel coherent-to-diffuse power ratio(CDR)covariance initialization and employing estimated value of the covariance matrix of the array received signals obtained by recursive averaging.The experimental results show that the improved MCLP algorithm is more effective by comparing different methods in different reverberation environments.
作者
周城旭
王冬霞
何冲
ZHOU Chengxu;WANG Dongxia;HE Chong(School of Electronic and Information Engineering,Liaoning University of Technology,Jinzhou,Liaoning 121001,China)
出处
《信号处理》
CSCD
北大核心
2021年第1期141-147,共7页
Journal of Signal Processing
基金
辽宁省科学事业公益研究基金项目(20170056)。
关键词
麦克风阵列
语音去混响
相干扩散功率比
多通道线性预测
microphone array
speech dereverbration
coherent-to-diffuse power ratio
multi-channel linear prediction
