Numerical recipes in C: the art of scientific computing
Numerical recipes in C: the art of scientific computing
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
A Robust Method for Speech Signal Time-Delay Estimation in Reverberant Rooms
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Time difference of arrival estimation of speech source in a noisy and reverberant environment
Signal Processing - Content-based image and video retrieval
Passive acoustic source localization for video camera steering
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
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
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Signal Processing
Particle filter with integrated voice activity detection for acoustic source tracking
EURASIP Journal on Applied Signal Processing
Elephant censusing via geophone arrays: a visual approach for linear arrays
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Low-cost sound-based localization using programmable mixed-signal systems-on-chip
Microelectronics Journal
Speaker Tracking Using Recursive EM Algorithms
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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A dual-step approach for speaker localization based on a microphone array is addressed in this paper. In the first stage, which is not the main concern of this paper, the time difference between arrivals of the speech signal at each pair of microphones is estimated. These readings are combined in the second stage to obtain the source location. In this paper, we focus on the second stage of the localization task. In this contribution, we propose to exploit the speaker's smooth trajectory for improving the current position estimate. Three localization schemes, which use the temporal information, are presented. The first is a recursive form of the Gauss method. The other two are extensions of the Kalman filter to the nonlinear problem at hand, namely, the extended Kalman filter and the unscented Kalman filter. These methods are compared with other algorithms, which do not make use of the temporal information. An extensive experimental study demonstrates the advantage of using the spatial-temporal methods. To gain some insight on the obtainable performance of the localization algorithm, an approximate analytical evaluation, verified by an experimental study, is conducted. This study shows that in common TDOA-based localization scenarios--where the microphone array has small interelement spread relative to the source position--the elevation and azimuth angles can be accurately estimated, whereas the Cartesian coordinates as well as the range are poorly estimated.