Acoustic Source Localization and Tracking Using Track Before Detect

M.F. Fallon, S. Godsill

Research output: Contribution to journalArticlepeer-review


Particle Filter-based Acoustic Source Localization algorithms attempt to track the position of a sound source - one or more people speaking in a room - based on the current data from a microphone array as well as all previous data up to that point. This paper first discusses some of the inherent behavioral traits of the steered beamformer localization function. Using conclusions drawn from that study, a multitarget methodology for acoustic source tracking based on the Track Before Detect (TBD) framework is introduced. The algorithm also implicitly evaluates source activity using a variable appended to the state vector. Using the TBD methodology avoids the need to identify a set of source measurements and also allows for a vast increase in the number of particles used for a comparitive computational load which results in increased tracking stability in challenging recording environments. An evaluation of tracking performance is given using a set of real speech recordings with two simultaneously active speech sources.
Original languageEnglish
Pages (from-to)1228-1242
Number of pages15
JournalIEEE Transactions on Audio, Speech and Language Processing
Issue number6
Publication statusPublished - 1 Aug 2010


  • acoustic signal processing
  • particle filtering (numerical methods)
  • speech processing
  • acoustic source localization
  • acoustic source tracking
  • particle filtering
  • steered beamformer localization function
  • track-before-detect
  • Acoustic source localization
  • multi-target tracking
  • sequential estimation
  • tracking filters

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