Nonconcurrent multiple speakers tracking based on extended Kalman particle filter

Abstract

Acoustic reverberation introduces multipath components into an audio signal, and therefore changes the source signal statistical properties. This causes problems for source localisation and tracking since reverberation generates spurious peaks in the time delay functions, and makes the subsequent location estimator hard to track the motion trajectory. Previous time delay based tracking methods, such as the extended Kalman filter and the particle filter, are sensitive to reverberation and are unable to follow sharp changes in the source positions. In this paper, the extended Kalman filter and the particle filter are combined to solve this problem. One of the advantages of this approach is that the optimal importance function can be obtained after extended Kalman filtering. Thus, the position samples are distributed in a more accurate area than using a prior importance function. Experiment results show that the proposed algorithm outperforms the sequential importance resampling particle filter by reducing the estimation error and following the switch of speakers quickly under a moderate reverberant environment (reverberation time T60 < 0.3s).