Using sound source localization in a home environment

In this paper, we examine the feasibility of sound source localization (SSL) in a home environment, and explore its potential to support inference of communication activity between people. Motivated by recent research in pervasive computing that uses a variety of sensor modes to infer high-level activity, we are interested in exploring how the relatively simple information of SSL might contribute. Our SSL system covers a significant portion of the public space in a realistic home setting by adapting traditional SSL algorithms developed for more highly-controlled lab environments. We describe engineering tradeoffs that result in a localization system with a fairly good 3D resolution. To help make design decisions for deploying a SSL system in a domestic environment, we provide a quantitative assessment of the accuracy and precision of our system. We also demonstrate how such a sensor system can provide a visualization to help humans infer activity in that space. Finally, we show preliminary results for automatic detection of face-to-face conversations.