Acoustic Source Localization and Tracking of a Time-Varying Number of Speakers

被引:51
|
作者
Fallon, Maurice F. [1 ]
Godsill, Simon J. [2 ]
机构
[1] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA
[2] Univ Cambridge, Dept Engn, Signal Proc & Commun Lab, Cambridge CB2 1PZ, England
关键词
Acoustic source location; multi-target tracking; particle filtering; sequential estimation; tracking filters;
D O I
10.1109/TASL.2011.2178402
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Particle filter-based acoustic source tracking algorithms track (online and in real-time) the position of a sound source-a person speaking in a room-based on the current data from a distributed microphone array as well as the previously recorded data. This paper develops a multi-target tracking (MTT) methodology to allow for an unknown and time-varying number of speakers in a fully probabilistic manner and in doing so does not resort to independent modules for new target proposal or target number estimation as in previous works. The approach uses the concept of an existence grid to propose possible regions of activity before tracking is carried out with a variable dimension particle filter-which also explicitly supports the concept of a null particle, containing no target states, when no speakers are active. Examples demonstrate typical tracking performance in a number of different scenarios with simultaneously active speech sources.
引用
收藏
页码:1409 / 1415
页数:7
相关论文
共 50 条
  • [21] Dynamic Underwater Acoustic Channel Tracking for Correlated Rapidly Time-Varying Channels
    Huang, Qihang
    Li, Wei
    Zhan, Weicheng
    Wang, Yuhang
    Guo, Rongrong
    IEEE ACCESS, 2021, 9 : 50485 - 50495
  • [22] Hand tracking in time-varying illumination
    Yao, Y
    Zhu, ML
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 4071 - 4075
  • [23] TRACKING IN LINEAR TIME-VARYING SYSTEMS
    KAMEN, EW
    PROCEEDINGS OF THE 1989 AMERICAN CONTROL CONFERENCE, VOLS 1-3, 1989, : 263 - 268
  • [24] 'Shadow BSS' for blind source separation in rapidly time-varying acoustic scenes
    Wehr, S.
    Lombard, A.
    Buchner, H.
    Kellermann, W.
    INDEPENDENT COMPONENT ANALYSIS AND SIGNAL SEPARATION, PROCEEDINGS, 2007, 4666 : 560 - +
  • [25] Tracking Channel Variations in a Time-varying Doubly-Spread Underwater Acoustic Channel
    Huang, S. H.
    Yang, T. C.
    Xu, W.
    OCEANS 2015 - MTS/IEEE WASHINGTON, 2015,
  • [26] Tracking of time-varying number of moving targets in wireless sensor fields by particle filtering
    Bugallo, Monica F.
    Djuric, Petar M.
    2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13, 2006, : 4535 - 4538
  • [27] Distributed Underwater Acoustic Source Localization and Tracking
    Yu, Jun Ye
    Uestebay, Deniz
    Blouin, Stephane
    Rabbat, Michael
    Coates, Mark
    2013 ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, 2013, : 634 - 638
  • [28] The LOCATA Challenge: Acoustic Source Localization and Tracking
    Evers, Christine
    Loellmann, Heinrich W.
    Mellmann, Heinrich
    Schmidt, Alexander
    Barfuss, Hendrik
    Naylor, Patrick A.
    Kellermann, Walter
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2020, 28 : 1620 - 1643
  • [29] An analytical investigation of the indirect measurement method of estimating the acoustic impedance of a time-varying source
    Peat, KS
    Ih, JG
    JOURNAL OF SOUND AND VIBRATION, 2001, 244 (05) : 821 - 835
  • [30] An analytical investigation of the direct measurement method of estimating the acoustic impedance of a time-varying source
    Peat, KS
    JOURNAL OF SOUND AND VIBRATION, 2002, 256 (02) : 271 - 285