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.