[1]ZHAO Dada,QI Xiaogang,FENG Hailin.Efficient acoustic source localization algorithm based on an inverse model[J].CAAI Transactions on Intelligent Systems,2023,18(1):117-123.[doi:10.11992/tis.202106010]
Copy
Efficient acoustic source localization algorithm based on an inverse model
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
18
Number of periods:
2023 1
Page number:
117-123
Column:
学术论文—人工智能基础
Public date:
2023-01-05
- Title:
- Efficient acoustic source localization algorithm based on an inverse model
- Keywords:
- conventional beamforming; time domain beamforming; generalized cross correlation; compression computational grid; inverse model; acoustic source localization; microphone array; density-based clustering
- CLC:
- TP391.9;TN912.3;TN641
- DOI:
- 10.11992/tis.202106010
- Abstract:
- Compared with the beamforming algorithm, the wideband acoustic source localization based on the generalized crosscorrelation inverse model provides a higher spatial resolution and requires more computation. This paper proposes an acceleration algorithm to improve the computational efficiency of acoustic source localization and retain the existing resolution. By removing the grid points with the low output power of the microphone array, the computational grid is compressed. The geometric factor is also considered, and the density-based clustering algorithm is used to further compress the grid. Finally, only the reserved points are used for the calculation to reduce the calculation scale. Experiments with real data show that the proposed algorithm can improve computational efficiency significantly.
- References:
-
[1] 李晓飞, 刘宏. 机器人听觉声源定位研究综述[J]. 智能系统学报, 2012, 7(1): 9–20
LI Xiaofei, LIU Hong. A survey of sound source localization for robot audition[J]. CAAI transactions on intelligent systems, 2012, 7(1): 9–20
[2] 鲍长春, 项扬. 基于深度神经网络的单通道语音增强方法回顾[J]. 信号处理, 2019, 35(12): 1931–1941
BAO Changchun, XIANG Yang. Review of monaural speech enhancement based on deep neural networks[J]. Journal of signal processing, 2019, 35(12): 1931–1941
[3] 高庆吉, 赵志华, 徐达, 等. 语音情感识别研究综述[J]. 智能系统学报, 2020, 15(1): 1–13
GAO Qingji, ZHAO Zhihua, XU Da, et al. Review on speech emotion recognition research[J]. CAAI transactions on intelligent systems, 2020, 15(1): 1–13
[4] MICHEL U. History of acoustic beamforming[C]//1. st Berlin beamforming conference. Berlin: DLR, 2006, 1–17.
[5] LI Jian, XIE Yao, STOICA P, et al. Beampattern synthesis via a matrix approach for signal power estimation[J]. IEEE transactions on signal processing, 2007, 55(12): 5643–5657.
[6] YAN Shefeng, SUN Haohai, SVENSSON U P, et al. Optimal modal beamforming for spherical microphone arrays[J]. IEEE transactions on audio, speech, and language processing, 2011, 19(2): 361–371.
[7] KUMAR L, HEGDE R M. Near-field acoustic source localization and beamforming in spherical harmonics domain[J]. IEEE transactions on signal processing, 2016, 64(13): 3351–3361.
[8] SALVATI D, DRIOLI C, FORESTI G L. A low-complexity robust beamforming using diagonal unloading for acoustic source localization[J]. IEEE/ACM transactions on audio, speech, and language processing, 2018, 26(3): 609–622.
[9] SIMARD P, ANTONI J. Acoustic source identification: experimenting the ?1 minimization approach[J]. Applied acoustics, 2013, 74(7): 974–986.
[10] LONG Tao, CHEN Jingdong, HUANG Gongping, et al. Acoustic source localization based on geometric projection in reverberant and noisy environments[J]. IEEE journal of selected topics in signal processing, 2019, 13(1): 143–155.
[11] PADOIS T, SGARD F, DOUTRES O, et al. Acoustic source localization using a polyhedral microphone array and an improved generalized cross-correlation technique[J]. Journal of sound and vibration, 2017, 386: 82–99.
[12] DOUGHERTY R, STOKER R. Sidelobe suppression for phased array aeroacoustic measurements[C]//4th AIAA/CEAS Aeroacoustics Conference. Toulouse: AIAA, 1998: 2242.
[13] BROOKS T F, HUMPHREYS W M. A deconvolution approach for the mapping of acoustic sources (DAMAS) determined from phased microphone arrays[J]. Journal of sound and vibration, 2006, 294(4/5): 856–879.
[14] SUN Dajun, MA Chao, MEI Jidan, et al. Improving the resolution of underwater acoustic image measurement by deconvolution[J]. Applied acoustics, 2020, 165: 107292.
[15] BAI Baohong, LI Xiaodong. Acoustic sources mapping based on the non-negative L1/2 regularization[J]. Applied acoustics, 2020, 169: 107456.
[16] MA Wei, LIU Xun. Compression computational grid based on functional beamforming for acoustic source localization[J]. Applied acoustics, 2018, 134: 75–87.
[17] KNAPP C, CARTER G. The generalized correlation method for estimation of time delay[J]. IEEE transactions on acoustics, speech, and signal processing, 1976, 24(4): 320–327.
[18] NO?L C, PLANEAU V, HABAULT D. A new temporal method for the identification of source directions in a reverberant hall[J]. Journal of sound and vibration, 2006, 296(3): 518–538.
[19] PADOIS T, DOUTRES O, SGARD F, et al. Time domain localization technique with sparsity constraint for imaging acoustic sources[J]. Mechanical systems and signal processing, 2017, 94: 85–93.
[20] CHU Zhigang, WENG Jing, YANG Yang. Determination of propagation model matrix in generalized cross-correlation based inverse model for broadband acoustic source localization[J]. The journal of the acoustical society of America, 2020, 147(4): 2098.
[21] VELASCO J, PIZARRO D, MACIAS-GUARASA J. Source localization with acoustic sensor arrays using generative model based fitting with sparse constraints[J]. Sensors, 2012, 12(10): 13781–13812.
[22] ESTER M, KRIEGEL H P, SANDER J, et al. A density-based algorithm for discovering clusters in large spatial databases with noise[C]// KDD’96: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining. Portland: AAAI, 1996, 34: 226?231.
[23] HADAD E, HEESE F, VARY P, et al. Multichannel audio database in various acoustic environments[C]//2014 14th International Workshop on Acoustic Signal Enhancement. Juan-les-Pins: IEEE, 2014: 313?317
- Similar References:
Memo
-
Last Update:
1900-01-01