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.