自适应信号处理，麦克风阵列信号处理，声场录制与重建

   

081002-信号与信息处理
085400-电子信息

音频信号处理
通信声学信号处理及应用

本课题组毕业生主要就业于华为、荣耀、腾讯、小米、快手等企业。课题组招生要求：（1）扎实的数学功底;（2）坚实的声学或数字信号处理基础;（3）较好的代码能力

2010-09--2013-07   中科院声学所   博士
2005-09--2008-03   东南大学   硕士
2001-09--2005-07   山东大学   学士

   

2016-04~2017-04,德国波鸿鲁尔大学通信声学研究所, 访问学者
2013-07~现在, 中国科学院声学研究所, 研究员
2008-03~2010-07,富迪科技（南京）有限公司, 高级工程师

通信声学前沿技术讲座
通信声学

   

（1） 北京市科学技术进步奖, 二等奖, 省级, 2020
（2） 中国科学院优秀博士论文奖, , 院级, 2016
（3） 中国科学院院长奖优秀奖, , 院级, 2013
（4） 中国科学院/北京市优秀毕业生, , 院级, 2013

（ 1 ） 无人机机载声学设备, 外观设计, 2024, 第 2 作者, 专利号: ZL 2023 3 0696282.3

（ 2 ） 基于深度自注意力神经网络分类器的合成语音检测方法, 发明专利, 2022, 第 3 作者, 专利号: 202210401440.2

（ 3 ） 多通道语音信号增强方法和装置及计算机设备和存储介质, 发明专利, 2022, 第 2 作者, 专利号: CN114882898A

（ 4 ） 一种低时延音频信号超定盲源分离方法及分离装置, 发明专利, 2022, 专利号: CN114863944A

（ 5 ） 一种车内抗干扰自适应路噪主动控制方法及控制系统, 发明专利, 2022, 第 2 作者, 专利号: CN114582312A

（ 6 ） 基于频域卷积传递函数的多通道非负矩阵分解方法及系统, 发明专利, 2022, 第 2 作者, 专利号: 202210031383.3

（ 7 ） 一种用于调节扬声器音量的多通道扩声系统及方法, 专利授权, 2021, 第 2 作者, 专利号: CN110830901B

（ 8 ） 一种低复杂度的频域盲分离方法及系统, 专利授权, 2019, 第 2 作者, 专利号: CN110010148A

（ 9 ） 一种无误差传声器的自适应主动降噪方法, 专利授权, 2018, 第 2 作者, 专利号: CN108428445A

（ 10 ） 一种基于卡尔曼滤波的去混响方法及系统, 专利授权, 2018, 第 2 作者, 专利号: CN108172231A

（ 11 ） 一种立体声音效增强系统, 发明专利, 2017, 第 1 作者, 专利号: CN106572419A

（ 12 ） 一种复数窄带干扰信号的频率估计及抑制装置及其方法, 专利授权, 2017, 第 2 作者, 专利号: CN106533999A

（ 13 ） 一种非平稳噪声环境下传声器阵列的语音增强方法, 发明专利, 2013, 第 2 作者, 专利号: CN103165137A

（ 14 ） 一种基于时间反转的声反馈抑制方法, 发明专利, 2012, 第 1 作者, 专利号: CN102740189A

（ 15 ） 一种基于反馈信号频谱估计的啸叫抑制方法, 发明专利, 2012, 第 1 作者, 专利号: CN102740214A

（ 16 ） 基于回声频谱估计和语音存在概率的立体声回声抵消方法, 发明专利, 2012, 第 1 作者, 专利号: CN102739886A

（ 17 ） 一种用于通信系统中的回声抵消方法, 发明专利, 2012, 第 1 作者, 专利号: CN102739286A

（ 18 ） 一种基于估计先验信噪比的多通道后置滤波方法及装置, 发明专利, 2024, 第 8 作者, 专利号: CN118366471A

（ 19 ） 一种非空气传导语音的恢复系统及方法, 发明专利, 2024, 第 2 作者, 专利号: CN117542373A

（ 20 ） 基于语音信号先验概率特性的语音信号增强方法及系统, 发明专利, 2024, 第 3 作者, 专利号: CN117373473A

（ 21 ） 一种低延时自适应声反馈消除方法及装置, 发明专利, 2023, 第 1 作者, 专利号: CN117241200A

（ 22 ） 一种时延估计系统及装置, 发明授权, 2023, 第 2 作者, 专利号: CN115798497B

期刊论文

[55] C. Li, F. Yang, and J. Yang, “Bone conduction-aided speech enhancement with two-tower network and contrastive learning,” IEEE Trans. Audio, Speech, Lang. Process., vol. 33, pp. 163–174, 2025.

[54] F. Yang, “Stochastic analysis of frequency-domain adaptive filters,” EURASIP Journal on Advances in Signal Process., 2024.

[53] C. Li, Y. Wan, F. Yang, and J. Yang, “Multi-scale information aggregation for spoofing detection,” EURASIP Journal on Audio, Speech, and Music Processing, 2024.

[52] H. Chen, W. Tan, J. Guo, and F. Yang, “SCANet: A lightweight deep learning network for massive MIMO CSI feedback based on spatial and channel attention mechanism,” Physical Communication, vol. 67, Dec. 2024.

[51] Z. Luo, Z. Yu, F. Kang, F. Yang, and J. Yang, “Performance analysis of unconstrained partitioned-block frequency-domain adaptive filters in under-modeling scenarios,” EURASIP Journal on Advances in Signal Process., vol. 2024, Aug. 2024.

[50] J. Hu, Y. Cao, M. Wu, Q. Kong, F. Yang, M. D. Plumbley, and J. Yang, “Selective-memory meta-learning with environment representations for sound event localization and detection,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 32, pp. 4313–4327, 2024.

[49] K. Kuang, F. Yang, and J. Yang, “A lightweight speech enhancement network fusing bone- and air-conducted speech,” J. Acoust. Soc. Amer., vol. 156, no. 2, pp. 1355–1366, Aug. 2024.

[48] J. Wang, F. Yang, X. Hu, and J. Yang, “Theoretical analysis of Maclaurin expansion based linear differential microphone arrays and improved solutions,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 32, pp. 3831–3835, 2024.

[47] Y. Liu, S. Liu, F. Yang, and J. Yang, “A deep hybrid model for stereophonic acoustic echo control,” Circuits Syst. Signal Process., 2024.

[46] S. Liu, F. Yang, R. Chen, and J. Yang, “Joint dereverberation and blind source separation using a hybrid autoregressive and convolutive transfer function-based model,” Applied Acoustics, vol. 224, 2024.

[45] T. Wang, F. Yang, and J. Yang, “Multi-channel linear prediction based speech dereverberation considering sparse and low-rank priors,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 32, pp. 1724–1735, 2024.

[44] C. Li, F. Yang, and J. Yang, “Restoration of bone-conducted speech with U-net-like model and energy distance loss,” IEEE Signal Process. Lett., vol. 31, pp. 166–170, 2024.

[43] J. Wang, F. Yang, Z. Yan, and J. Yang, “Design of frequency-invariant uniform concentric circular arrays with first-order directional microphones,” Signal Process., vol. 217, Apr. 2024.

[42] Q. Shi, J. Wang, F. Yang, and J. Yang, “A note on the design of frequency-invariant beamformer with uniformly concentric circular microphone array,” Applied Acoustics, vol. 217, Feb. 2024.

[41] C. Li, F. Yang, and J. Yang, “A two-stage approach to quality restoration of bone-conducted speech,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 32, pp. 818–829, 2024.

[40] J. Wang, F. Yang, J. Li, H. Sun, and J. Yang, “Mode matching based beamforming with frequency-wise truncation order for concentric circular differential microphone arrays,” J. Acoust. Soc. Amer., vol. 154, no. 6, pp. 3931–3940, Dec. 2023.

[39] J. Wang, F. Yang, and J. Yang, “A general approach to the design of the fractional-order superdirective beamformer,” IEEE Trans. Circuits Syst. II, vol.70, no. 11, pp. 4291–4295, Nov. 2023.

[38] K. Kuang, F. Yang, J. Li, and J. Yang, “Three-stage hybrid neural beamformer for multi-channel speech enhancement,” J. Acoust. Soc. Amer., vol. 153, no. 6, pp. 3378–3389, Jun. 2023.

[37] J. Wang, F. Yang, and J. Yang, “A perspective on fully steerable differential beamformers for circular arrays,” IEEE Signal Process. Lett., vol. 30, pp. 648–652, May 2023.

[36] J. Wang, F. Yang, and J. Yang, “Insights into the MMSE-based frequency-invariant beamformers for uniform circular arrays,” IEEE Signal Process. Lett., vol. 29, pp. 2432–2436, Dec. 2022.

[35] F. Yang, “Analysis of unconstrained partitioned-block frequency-domain adaptive filters,” IEEE Signal Process. Lett., vol. 29, pp. 2377–2381, Nov. 2022.

[34] T. Wang, F. Yang, N. Li, C. Zhang, and J. Yang, “Low-latency independent vector analysis using convolutive transfer function,” Applied Acoustics, vol. 197, Aug. 2022.

[33] C. Li, F. Yang, and J. Yang, “The role of long-term dependency in synthetic speech detection,” IEEE Signal Process. Lett., vol. 29, pp. 1142–1146, Apr. 2022.

[32] T. Wang, F. Yang, and J. Yang, “Convolutive transfer function-based multichannel nonnegative matrix factorization for overdetermined blind source separation,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 30, pp. 802–815, Jan. 2022.

[31] F. Yang, “Analysis of deficient-length partitioned-block frequency-domain adaptive filters,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 30, pp. 456–467, Jan. 2022.

[30] F. Yang, G. Enzner, and J. Yang, “On the convergence behavior of partitioned-block frequency-domain adaptive filters,” IEEE Trans. Signal Process., vol. 69, pp. 4906–4920, Aug. 2021.

[29] S. Liu, F. Yang, Y. Cao, and J. Yang, “Frequency-dependent auto-pooling function for weakly supervised sound event detection,” EURASIP Journal on Audio, Speech, and Music Processing, 2021.

[28] F. Yang, G. Enzner, and J. Yang, “New insights into convergence theory of constrained frequency-domain adaptive filters,” Circuits Syst. Signal Process., vol. 40, pp. 2076–2090, Apr. 2021.

[27] Z. Yan, F. Yang, and J. Yang, “Optimum step-size control for a variable step-size stereo acoustic echo canceller in the frequency domain,” Speech Communication, vol. 124, pp. 21–27, Nov. 2020.

[26] F. Yang, J. Guo, and J. Yang, “Stochastic analysis of the filtered-x LMS algorithm for active noise control,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 28, pp. 2252–2266, 2020.

[25] J. Guo, F. Yang, and J. Yang, “Mean-square performance of the modified FxAP algorithm for active noise control,” Circuit Syst. Signal Process., vol. 39, no. 8, pp. 4243–4257, Aug. 2020.

[24] J. Guo, F. Yang, and J. Yang, “Convergence analysis of the conventional filtered-x affine projection algorithm for active noise control,” Signal Process., vol. 170, May, 2020.

[23] C. Lu, F. Yang, and J. Yang, “An adaptive time-domain Kalman filtering approach to acoustic feedback cancellation for hearing aids,” Chinese Journal of Electronics, pp. 139–146, Jan. 2020.

[22] F. Kang, F. Yang, and J. Yang, “A low-complexity permutation alignment method for frequency-domain blind source separation,” Speech Communication, vol. 115, pp. 88–94, Dec. 2019.

[21] F. Yang and J. Yang, “Convergence analysis of deficient-length frequency-domain adaptive filters,” IEEE Trans. Circuits Syst. I, vol. 66, no. 11, pp. 4242–4255, Nov. 2019.

[20] F. Yang and J. Yang, “Mean-square performance of the modified frequency-domain block LMS algorithm,” Signal Process., vol. 163, pp 18–25, Oct. 2019.

[19] Y. Qi, F. Yang, M, Wu, and J. Yang, “A broadband Kalman filtering approach to blind multichannel identification,” IEICE Trans. Fundamentals, vol. E102-A, pp.788–795, June 2019.

[18] F. Yang, G. Enzner, and J. Yang, “A unified approach to the statistical convergence analysis of frequency-domain adaptive filters,” IEEE Trans. Signal Process., vol. 67, pp. 1785–1796, Apr. 2019.

[17] F. Yang, Y. Cao, M. Wu, F. Albu, and J. Yang, “Frequency-domain filtered-x LMS algorithms for active noise control: a review and new insights,” Applied Sciences, vol. 8, no. 11, 2018.

[16] F. Yang and J. Yang, “A comparative survey of fast affine projection algorithms,” Digital Signal Process., vol. 83, pp. 297–322, Dec. 2018.

[15] F. Yang and J. Yang, “Multiband-structured Kalman filter,” IET Signal Process., vol. 12, no. 6, pp. 722–728, Aug. 2018.

[14] F. Yang and J. Yang, “Optimal step-size control of the partitioned block frequency-domain adaptive filter,” IEEE Trans. Circuits Syst. II, vol. 65, no. 6, pp. 814–818, Jun. 2018.

[13] Q. Feng, F. Yang, and J. Yang, “Time-domain sound field reproduction using the group Lasso,” J. Acoust. Soc. Amer., vol. 143. No. 2. pp. EL55–EL60, Feb. 2018.

[12] Q. Feng, F. Yang, and J. Yang, “Interpolation of the early part of the acoustic transfer functions using block sparse models,” J. Acoust. Soc. Amer.,vol. 142, no. 6, pp. EL532–EL536, Dec. 2017.

[11] F. Yang, G. Enzner, and J. Yang, “Frequency-domain adaptive Kalman filter with fast recovery of abrupt echo-path changes,” IEEE Signal Process. Lett., vol. 24, no. 12, pp. 1778–1782, Dec. 2017.

[10] Z. Yan, F. Yang, and J. Yang, “Block sparse reweighted zero-attracting normalised least mean square algorithm for system identification,” Electronics Letters, vol. 53, pp. 899–900, July 2017.

[9] F. Yang, G. Enzner, and J. Yang, “Statistical convergence analysis for optimal control of DFT-domain adaptive echo canceler,” IEEE/ACM Trans. Audio, Speech, Lang. Process., vol. 25, no. 5, pp. 1095–1106, May 2017.

[8] R. Zhu, F. Yang, and J. Yang, “A gradient-adaptive lattice based complex adaptive notch filter,” EURASIP Journal on Advances in Signal Process., 2016.

[7] R. Zhu, F. Yang, and J. Yang, “An RLS-based Lattice-form complex adaptive notch filter,” IEEE Signal Process. Lett., vol. 23, no. 2, pp.217–221, Feb. 2016.

[6] F. Yang, M. Wu, P. Ji, and J. Yang, “Low-complexity implementation of the improved multiband-structured subband adaptive filter algorithm,” IEEE Trans. Signal Process., pp. 5133–5148, 2015.

[5] F. Yang, M. Wu, P. Ji, Z. Kuang, and J. Yang, “Transient and steady-state analyses of the improved multiband-structured subband adaptive filter algorithm,” IET Signal Process., pp. 596–604, 2015.

[4] F. Yang, M. Wu, J. Yang, and Z. Kuang, “A fast exact filtering approach to a family of affine projection-type algorithms,” Signal Process., vol. 101, pp. 1–10, Aug. 2014.

[3] F. Yang, M. Wu, and J. Yang, “A computationally efficient delayless frequency-domain adaptive filter algorithm,” IEEE Trans. Circuits Syst. II, vol. 60, no. 4, pp. 222–226, Apr. 2013.

[2] F. Yang, M. Wu, P. Ji, and J. Yang, “An improved multiband-structured subband adaptive filter algorithm,” IEEE Signal Process. Lett., vol. 19, no. 10, pp.647–650, Oct. 2012.

[1] F. Yang, M. Wu, and J. Yang, “Stereophonic acoustic echo suppression based on Wiener filter in the short-time Fourier transform domain,” IEEE Signal Process. Lett., pp. 227–230, Apr. 2012.