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基于辅助函数独立分量分析的频域声回波消除
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作者单位:

南京信息工程大学

中图分类号:

TN912????

基金项目:

国家自然科学基金(12074192)


Frequency domain acoustic echo cancellation using auxiliary function based independent component analysis
Author:
Affiliation:

1.Nanjing University of Information Science &2.Technology

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    摘要:

    传统的声回波消除(Acoustic Echo Cancellation, AEC)方法使用双端通话检测器判断单、双端通话场景，性能受限。盲源分离(Blind Source Separation, BSS)信号模型是一个远端和近端信号并存的全双工模型,因此基于BSS的AEC无需双端通话检测器。本文采用基于辅助函数的独立分量分析(Auxiliary Function Based Independent Component Analysis, Aux-ICA)算法在频域上实现声回波消除，以最小化互信息为目标函数，借助辅助函数技术进行优化。仿真实验结果表明，在连续的双端通话场景中，该方法具有较低的计算复杂度和较好的回波消除性能。

    Abstract:

    Traditional AEC’s performance is restricted when using double-talk detector to determine the double- talk and single-talk scenarios. Blind source separation signal model is a full duplex model with both far-end and near-end signals, so AEC based on BSS does not need the double-talk detector. This paper adopts auxiliary function based independent component analysis algorithm to realize acoustic echo cancellation in frequency domain. The object function of Aux-ICA is minimizing the mutual information, and the auxiliary function technique is used for the optimization. Simulation results show that this method has lower computational complexity and better acoustic echo cancellation performance in the continuous double-talk scenarios.

    参考文献
    [1] 张琦,王霞,薛涛.自适应回波抵消中变步长NLMS算法的研究[J].数据采集与处理,2013,28(1): 64-68.HANG Qi, WANG Xia, XUE Tao. Variable Step-Size NLMS Algorithms in Echo cancellation [J]. Data Acquisition and Processing, 2013,28(1): 64-68.
    [2] Morgan D R and Kratzer S G. On a class of computationally efficient, rapidly converging, generalized NLMS algorithms. IEEE Signal Processing Letters, 1996, 3(8): 245-247.
    [3] Albu I, Anghel C and Paleologu C. Adaptive filtering in acoustic echo cancellation systems-A practical overview [C]// 2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). Targoviste, Romania: IEEE Press, 2017: 1-6.
    [4] Valin J. On Adjusting the Learning Rate in Frequency Domain Echo Cancellation With Double-Talk [J]. IEEE Transactions on Audio, Speech, and Language Processing, 2007, 15(3): 1030-1034.
    [5] Yang Jun. Multilayer Adaptation Based Complex Echo Cancellation and Voice Enhancement [C]// 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Calgary, AB, Canada: IEEE Press, 2018: 2131-2135.
    [6] 丁锋.辅助模型辨识方法(5):最小二乘辨识[J].南京信息工程大学学报(自然科学版),2016,8(05):385-403.ING feng. Auxiliary model based identification methods．Part E: Least squares identification[J]. Journal of Nanjing University of Information Science Technology: Natural Science Edition, 2016,8(05):385-403.
    [7] 杨果, 王亚洁, 王晶. Speex编码器中回声消除算法的分析与评估[J]. 电声技术, 2013, 37(9): 52-55.ANG Guo, WANG Yajie, WANG Jing. The analysis and evaluation of echo cancellation algorithm in Speex encoder [J]. Audio Engineering, 2013, 37(9): 52-55.
    [8] Ono N, Miyabe S. Auxiliary-Function-Based Independent Component Analysis for Super- Gaussian Sources [C]// International conference on latent variable analysis and signal separation. Berlin, Heidelberg: Springer, 2010: 165-172.
    [9] Gunther J. Learning Echo Paths During Continuous Double-Talk Using Semi-Blind Source Separation [J].IEEE Transactions on Audio, Speech, and Language Processing, 2012, 20(2): 646-660.
    [10] M. Z. Ikram. Blind source separation and acoustic echo cancellation: A unified framework [C]// 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Kyoto, Japan: IEEE Press,2012: 1701-1704.
    [11] 张艳萍,李杰.回波对消中盲源分离算法的研究与仿真[J].南京信息工程大学学报(自然科学版),2013,5(06):539-543.HANG Yanping, LI Jie. Optimization and simulation of blind source separation in acoustic echo cancellation[J]. Journal of Nanjing University of Information Science Technology: Natural Science Edition, 2013,5(06):539-543.
    [12] 石怀涛,周乾,王雨桐,等.基于相对变换的ICA故障检测方法[J].电子测量与仪器学报,2017,31(7):1040-1046.HI Huaitao, ZHOU Qian, WANG Yutong, et al. Fault detection method based on relative-transformation ICA[J]. Journal of Electronic Measurement and Instrument, 2017,31(7):1040-1046.
    [13] Scheibler R and Ono N. Independent Vector Analysis with More Microphones Than Sources [C]// 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). New Paltz, NY, USA: IEEE Press, 2019: 185-189.
    [14] Lei Q, Chen H, Hou J, et al. Deep Neural Network Based Regression Approach for Acoustic Echo Cancellation[C]//ICMSSP 2019: 2019 4th International Conference on Multimedia Systems and Signal Processing, Guangzhou China, May, 2019.
    [15] 周晓彦,王珂,李凌燕.基于深度学习的目标检测算法综述[J].电子测量技术,2017,40(11):89-93.HOU Xiaoyan, WANG Ke, LI Lingyan. Review of object detection based on deep learning[J]. Electronic Measurement Technology, 2017,40(11):89-93.
    [16] Taniguchi T, Ono N, Kawamura A, et al. An auxiliary-function approach to online independent vector analysis for real-time blind source separation [C]// 2014 4th Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA). Villers-les-Nancy, France: IEEE Press, 2014: 107-111.
    [17] Ono N. Auxiliary-function-based indepen- dent vector analysis with power of vector-norm type weighting functions [C]// Proceedings of The 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference. Hollywood, CA, USA:IEEE Press, 2012:1-4.
    [18] 魏本征,甘洁,尹义龙.基于边缘特征点互信息熵的医学图像配准方法[J].数据采集与处理,2018,33(2):248-258.EI Benzheng, GAN Jie, YIN Yilong. Medical Image Registration Based on Mutual Information Entropy Combined with Edge Correlation Feature [J]. Data Acquisition and Processing, 2018,33(2):248-258.
    [19] 姜波,杨军,张尔扬.稀疏自适应Volterra滤波的QRD-RLS算法[J].信号处理,2008(04):595-599.IANG Bo, YANG Jun, ZHANG Eryang. QRD-RLS Algorithm for Sparse Adaptive Volterra filtering[J]. Signal Processing, 2008(04):595-599.
    [20] Allen, Jont B and Berkley D A. Image method for efficiently simulating small-room acoustics [J]. The Journal of the Acoustical Society of America, 1979, 65(4): 943-950.
    [21] Loizou P C. Speech enhancement: theory and practice[M]. Florida: CRC Press, 2007: 492–495.
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吴礼福,王雷,孙芯年,孙帅恒.基于辅助函数独立分量分析的频域声回波消除[J].南京信息工程大学学报,,():

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  • 收稿日期:2022-02-22
  • 最后修改日期:2022-03-26
  • 录用日期:2022-03-28

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