Multi Target Acoustic Source Tracking with an Unknown and Time Varying Number of Targets

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 all previous data up to that point. This paper develops a previously introduced multi-target (MTT) methodology to allow for an unknown and time-varying number of speakers. Finally examples show typical tracking performance in a number of different scenarios with simultaneously active speech sources.

[1]  Maurice Fallon,et al.  Multi Target Acoustic Source Tracking using Track Before Detect , 2007, 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

[2]  D. J. Salmond,et al.  A particle filter for track-before-detect , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[3]  Simon J. Godsill,et al.  An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo , 2007, Proceedings of the IEEE.

[4]  Mark R. Morelande,et al.  A Bayesian Approach to Multiple Target Detection and Tracking , 2007, IEEE Transactions on Signal Processing.

[5]  Andrew Blake,et al.  Nonlinear filtering for speaker tracking in noisy and reverberant environments , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[6]  Simon J. Godsill,et al.  Multitarget Initiation, Tracking and Termination Using Bayesian Monte Carlo Methods , 2007, Comput. J..

[7]  Eric A. Lehmann,et al.  Particle Filter Design Using Importance Sampling for Acoustic Source Localisation and Tracking in Reverberant Environments , 2006, EURASIP J. Adv. Signal Process..

[8]  Darren B. Ward,et al.  Particle filtering algorithms for tracking an acoustic source in a reverberant environment , 2003, IEEE Trans. Speech Audio Process..