Environment situation reasoning integrating human recognition and life sound recognition using DBN

Humanoid robots for home daily assistance need to have an autonomous behavior selection system. To realize this, situation recognition capability is important. In this paper, we propose a situation recognition system where the use of daily life sounds enables to recognize situations difficult to understand using only visual sensor data and where the use of time series of information enables robust situation recognition. We apply cepstrum feature for recognition of daily life sounds and Dynamic Bayesian Networks(DBN) for robust situation recognition. As an example of situation recognition, we show some experiments and results targeting some situations that a human is in a kitchen.