Context aware sound event recognition for home service robots
Sound event recognition without the context is challenging for both humans and robots due to the diversity of sound events. Contextual information allows them to disambiguate the sound events, for example, in a home environment. This paper proposes and implements a context aware sound event recognition for a home service robot that monitors the elderly living alone at home. The location context of sound events is estimated by fusing distributed PIR (Passive Infrared) Sensors. A two level dynamic Bayesian network (DBN) is used to model the intra temporal and inter temporal constraints among the context and sound events. We conducted experiments in a robot integrated smart home (RiSH) testbed to evaluate the proposed method. The obtained results show the effectiveness and accuracy of context aware sound event recognition.
2016 IEEE International Conference on Automation Science and Engineering (CASE)