Speaker Tracking Using Recursive EM Algorithms

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.