摘要
给出了一种频域合成房间频率响应的方法用于卷积法人工混响,基于频域内房间频率响应的后期部分为高斯随机过程的假设,用自回归滑动平均模型为其自协方差函数和功率谱密度进行参数化描述,在对自回归滑动平均模型中的参数求解后,通过逆滤波得到了房间频率响应后期部分,与房间频率响应前期部分组合后经过傅里叶反变换得到完整的房间脉冲响应。仿真结果表明该方法的混响效果与镜像源法接近,明显优于反馈延迟网络法,但其计算复杂度比镜像源法低,便于实时应用。
A convolution based arti cial reverberation method is introduced,where the late part of the room frequency response is modelled as a complex Gaussian random process in the frequency domain,the auto-covariance function and power spectral density are parameterized by an autoregressive moving average(ARMA)model.Then the ARMA parameters are estimated and the room frequency response is obtained by inverse ltering in the frequency domain.The time domain room impulse response is nally obtained using the inverse Fourier transform of the room frequency response.Simulation results show that the introduced method gives better reverberation e ect than the feedback delay network method,while it has lower computational complexity than the image source method,thus could be used in real time applications.
作者
吴礼福
陶明明
郭业才
WU Lifu;TAO Mingming;GUO Yecai(School of Electronic&Information Engineering,Nanjing University of Information Science&Technology,Nanjing 210044,China;Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology,Nanjing 210044,China)
出处
《应用声学》
CSCD
北大核心
2020年第2期163-168,共6页
Journal of Applied Acoustics
基金
国家自然科学基金项目(11504176)。
关键词
人工混响
自回归滑动平均
反馈延迟网络
镜像源
Arti cial reverberation
Autoregressive moving average
Feedback delay network
Image source