TRAMP: Tracking by a Real-time AMbisonic-based Particle filter
This incremental work provides a real-time system for sound source tracking, useful for applications in audio processing and robotics.
The paper tackles real-time multiple sound source localization and tracking using an Eigenmike array and First Order Ambisonics, resulting in a fully-functional system that can serve as a baseline for the LOCATA challenge.
This article presents a multiple sound source localization and tracking system, fed by the Eigenmike array. The First Order Ambisonics (FOA) format is used to build a pseudointensity-based spherical histogram, from which the source position estimates are deduced. These instantaneous estimates are processed by a wellknown tracking system relying on a set of particle filters. While the novelty within localization and tracking is incremental, the fully-functional, complete and real-time running system based on these algorithms is proposed for the first time. As such, it could serve as an additional baseline method of the LOCATA challenge.