Convex Optimization
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
Tracking of multiple moving sources using recursive EM algorithm
EURASIP Journal on Applied Signal Processing
Kalman filters for time delay of arrival-based source localization
EURASIP Journal on Applied Signal Processing
Microphone array speaker localizers using spatial-temporal information
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Signal Processing
Binaural Tracking of Multiple Moving Sources
IEEE Transactions on Audio, Speech, and Language Processing
Recursive estimation of prior probabilities using a mixture
IEEE Transactions on Information Theory
IEEE Transactions on Audio, Speech, and Language Processing
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The problem of localizing and tracking a known number of concurrent speakers in noisy and reverberant enclosures is addressed in this paper. We formulate the localization task as a maximum likelihood (ML) parameter estimation problem, and solve it by utilizing the expectation-maximization (EM) procedure. For the tracking scenario, we propose to adapt two recursive EM (REM) variants. The first, based on Titterington's scheme, is a Newton-based recursion. In this work we also extend Titterington's method to deal with constrained maximization, encountered in the problem at hand. The second is based on Cappé and Moulines' scheme. We discuss the similarities and dissimilarities of these two variants and show their applicability to the tracking problem by a simulated experimental study.