Predictive acoustic localization and speaker tracking for distributed sensor networks

Acoustic source localization has a variety of applications, from speech signal enhancement to mobile object tracking. Localization procedures applying lightweight algorithms are appealing for implementation in distributed embedded systems. This paper builds on our previous research of simplifying acoustic localization based on the Steered Response Power with Phase Transform (SRP-PHAT) algorithm and proposes further enhancement by introducing object trajectory tracking and coordinate prediction. For these purposes we integrate Kaiman and Rao-Blackwellized particle filters into our simplified approach. Filter predictions serve as target areas for acoustic source search during the subsequent time frames, supporting localization. The approach is applied to moving speaker tracking and displays promising results.