基于双麦克风模型的MPNLMS声反馈抑制算法
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摘要
在单个麦克风的声反馈抑制系统中,基于μ准则的比例归一化最小均方(Proportionate normalized least mean square based onμ-law, MPNLMS)算法由于步长控制矩阵更优,总体收敛速度快,被广泛应用于声反馈抑制技术,但MPNLMS算法对滤波器系数的有偏估计会显著地降低其性能。针对上述问题,提出一种基于双麦克风模型的MPNLMS算法,系统中副麦克风估计主麦克风的有效输入信号,将估计信号与主麦克风输出信号相减之后所得的误差信号用于自适应滤波器系数的更新。仿真结果表明,提出的基于双麦克风模型的MPNLMS算法不再受制于扬声器输出信号与有效信号之间的相关性,而且上述算法的收敛速度、误差与最大增益均优于传统单个麦克风声反馈抑制系统中的MPNLMS算法。
In single microphone acoustic feedback cancellation system, due to that the step control matrix is better and the convergence speed is fast, proportionate normalized least mean square based on μ-law(MPNLMS) algorithm is widely used in acoustic feedback cancellation(AFC). However, the biased estimation of the filter's coefficients significantly reduces the performance of MPNLMS algorithm. To solve this problem,a MPNLMS algorithm based on two microphone acoustic feedback cancellation system is proposed. The added microphone can provide added information to obtain an incoming signal estimate. This estimate was removed from the primary microphone signal to create the error signal which adapted the canceler's coefficients. The simulation shows that the proposed algorithm is no longer subject to the correlation between the loudspeaker and incoming signal, it has faster convergence speed and better max stable gain and misalignment performance than MPNLMS.
In single microphone acoustic feedback cancellation system, due to that the step control matrix is better and the convergence speed is fast, proportionate normalized least mean square based on μ-law(MPNLMS) algorithm is widely used in acoustic feedback cancellation(AFC). However, the biased estimation of the filter's coefficients significantly reduces the performance of MPNLMS algorithm. To solve this problem,a MPNLMS algorithm based on two microphone acoustic feedback cancellation system is proposed. The added microphone can provide added information to obtain an incoming signal estimate. This estimate was removed from the primary microphone signal to create the error signal which adapted the canceler's coefficients. The simulation shows that the proposed algorithm is no longer subject to the correlation between the loudspeaker and incoming signal, it has faster convergence speed and better max stable gain and misalignment performance than MPNLMS.
引文
[1] A Spriet,G ombouts,M Moonen,and J Wouters.Adaptive feedback cancellation in hearing aids[J].Franklin Inst,2006,343(6):545-573.
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[4] D L Duttweiler.Proportionate normalized least-mean squares adaptation in echo cancelers[J].IEEE Transactions on Speech and Audio Processing,2000,8(5):508-518.
[5] R L Das,M Chakraborty.Improving t-he Performance of the PNLMS Algorithm Using l1 Norm Regularization[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2016,24(7):1280-1290.
[6] H Deng,M Doroslovacki.Improving c-onvergence of the PNLMS algorithm for sparse impulse response identification[J].IEEE Signal Processing Letters,2005,12(3):181-184.
[7] 郭继昌,张雪,邱琳耀.一种改进的PNLMS自适应滤波算法[J].天津大学学报(自然科学与工程技术版),2016,49(9):972-977.
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[9] L T T Tran,H Schepker,S Doclo,H H Dam,S Nordholm.Proportionate NLMS for adaptive feedback control in hearing aids[C].IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),2017:211-215.
[10] C R C Nakagawa,S Nordholm,W Y Yan.Dual microphone solution for acoustic feedback cancellation for assistive listening[C].IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP),2012:149-152.
[11] T Elmedyb,J Hellgren.Hearing aid system with feedback arrangement to predict and cancel acoustic feedback,method and use[P].WO Patent,2009.
[12] C R C Nakagawa,S Nordholm,W Y Yan.Analysis of two microphone method for feedback cancellation[J].IEEE Signal Processing Letters,2015,22(1):35-39.
[13] L Ljung.System Identification Theory for the User[M].USA:Upper Saddle River,Prentice-Hall,1999.
[14] L T T Tran,S Nordholm,H H Dam,W Y Yan,C R Nakagawa.Acoustic Feedback Cancellation in Hearing Aids Using Two Microphones Employing Variable Step Size Affine Projection Algorithms[C].IEEE International Conference on Digital Signal Processing (DSP),2015:1191-1195.
[15] C R C Nakagawa,S Nordholm,F Albu,and W Y Yan.Closed-loop feedback cancellation utilizing two microphones and transform domain processing[C].IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP),2014:3645-3649.
[16] P C Loizou.Speech Enhancement:Theory and Practice[M].USA:CRC Press,Inc,Boca Raton,FL,2007.
[17] L T T Tran,H H Dam,H Schepker,S Doclo,S E Nordholm.Evaluation of two-microphone acoustic feedback cancellation using uniform and non-uniform sub-bands in hearing aids[C].Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA),2015:308-313.
[2] U Forssell,L Ljung.Closed-loop identifyca-tion revisited[J].Automatic,1999,35(7):1215-1241.
[3] 尹浩琼.通信系统中回声消除的研究[D].北京邮电大学,2006.
[4] D L Duttweiler.Proportionate normalized least-mean squares adaptation in echo cancelers[J].IEEE Transactions on Speech and Audio Processing,2000,8(5):508-518.
[5] R L Das,M Chakraborty.Improving t-he Performance of the PNLMS Algorithm Using l1 Norm Regularization[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2016,24(7):1280-1290.
[6] H Deng,M Doroslovacki.Improving c-onvergence of the PNLMS algorithm for sparse impulse response identification[J].IEEE Signal Processing Letters,2005,12(3):181-184.
[7] 郭继昌,张雪,邱琳耀.一种改进的PNLMS自适应滤波算法[J].天津大学学报(自然科学与工程技术版),2016,49(9):972-977.
[8] L Liu,M Fukumoto,S Zhang.Improv-ement of the μ-law proportionate NLMS algorithm[C].IEEE International Symposium on Circuits and Systems (ISCAS),2009:2045-2048.
[9] L T T Tran,H Schepker,S Doclo,H H Dam,S Nordholm.Proportionate NLMS for adaptive feedback control in hearing aids[C].IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),2017:211-215.
[10] C R C Nakagawa,S Nordholm,W Y Yan.Dual microphone solution for acoustic feedback cancellation for assistive listening[C].IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP),2012:149-152.
[11] T Elmedyb,J Hellgren.Hearing aid system with feedback arrangement to predict and cancel acoustic feedback,method and use[P].WO Patent,2009.
[12] C R C Nakagawa,S Nordholm,W Y Yan.Analysis of two microphone method for feedback cancellation[J].IEEE Signal Processing Letters,2015,22(1):35-39.
[13] L Ljung.System Identification Theory for the User[M].USA:Upper Saddle River,Prentice-Hall,1999.
[14] L T T Tran,S Nordholm,H H Dam,W Y Yan,C R Nakagawa.Acoustic Feedback Cancellation in Hearing Aids Using Two Microphones Employing Variable Step Size Affine Projection Algorithms[C].IEEE International Conference on Digital Signal Processing (DSP),2015:1191-1195.
[15] C R C Nakagawa,S Nordholm,F Albu,and W Y Yan.Closed-loop feedback cancellation utilizing two microphones and transform domain processing[C].IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP),2014:3645-3649.
[16] P C Loizou.Speech Enhancement:Theory and Practice[M].USA:CRC Press,Inc,Boca Raton,FL,2007.
[17] L T T Tran,H H Dam,H Schepker,S Doclo,S E Nordholm.Evaluation of two-microphone acoustic feedback cancellation using uniform and non-uniform sub-bands in hearing aids[C].Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA),2015:308-313.