Page 5 - 《应用声学》2020年第2期
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第 39 卷 第 2 期                                                                       Vol. 39, No. 2
             2020 年 3 月                          Journal of Applied Acoustics                    March, 2020

             ⋄ 研究报告 ⋄



                      频域合成房间频率响应的人工混响方法                                                          ∗




                                          吴礼福      1,2†  陶明明     1   郭业才      1,2


                                        (1  南京信息工程大学电子与信息工程学院           南京   210044)
                                        (2  江苏省大气环境与装备技术协同创新中心           南京  210044)

                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。
                关键词：人工混响；自回归滑动平均；反馈延迟网络；镜像源
                中图法分类号: O429           文献标识码: A          文章编号: 1000-310X(2020)02-0163-06
                DOI: 10.11684/j.issn.1000-310X.2020.02.001



                       Artificial reverberation by synthesizing room frequency response

                                              in the frequency domain


                                       WU Lifu  1,2  TAO Mingming 1  GUO Yecai  1,2

                    (1 School of Electronic & Information Engineering, Nanjing University of Information Science & Technology,
                                                    Nanjing 210044, China)
                       (2 Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology,
                                                    Nanjing 210044, China)

                 Abstract: A convolution based artificial 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
                 filtering in the frequency domain. The time domain room impulse response is finally obtained using the inverse
                 Fourier transform of the room frequency response. Simulation results show that the introduced method gives
                 better reverberation effect 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.
                 Keywords: Artificial reverberation; Autoregressive moving average; Feedback delay network; Image source






             2019-06-24 收稿; 2019-10-23 定稿
             国家自然科学基金项目 (11504176)
             ∗
             作者简介: 吴礼福 (1981– ), 男, 安徽全椒人, 博士, 副教授, 研究方向: 音频信号处理。
              通信作者 E-mail: wulifu@nuist.edu.cn
             †
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