Tracking and data association
Tracking Multiple Talkers Using Microphone-Array Measurements
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
A framework for speech source localization using sensor arrays
A framework for speech source localization using sensor arrays
Nonlinear filtering for speaker tracking in noisy and reverberant environments
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Multi- and single view multiperson tracking for smart room environments
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
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Automatic speaker localization is an important task in several applications such as acoustic scene analysis, hands-free videoconferencing or speech enhancement. Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this work, we present the acoustic Person Tracking system developed at the UPC for the CLEAR'07 evaluation campaign. The designed system is able to track the estimated position of multiple speakers in a smart-room environment. Preliminary speaker locations are provided by the SRP-PHAT algorithm, which is known to perform robustly in most scenarios. Data association techniques based on trajectory prediction and spatizal clustering are used to match the raw positional estimates with potential speakers. These positional measurements are then finally spatially smoothed by means of Kalman filtering. Besides the technology description, experimental results obtained on the CLEAR'07 CHIL database are also reported.