Speech-based localization of multiple persons for an interface robot

Robots are conveniently controlled by a human operator with spoken commands, since voice is a natural communication medium for humans. In order to successfully carry out a command, a robot needs to know which of the possibly many people gave the command and where this person is located. In this paper, we present a particle-filter based algorithm for localization of multiple speakers, in an environment where there is only one person speaking at a time. The algorithm incorporates person-specific voice features (vowel formant frequencies) in order to distinguish between the speakers. The voice features are supported by azimuth angle measurements obtained by a pair of microphones. We test our approach using the microphone system of the Philips iCat interface robot.