Speaker's Gender Identification for Human-Robot Interaction

This paper is concerned with a text-independent Speaker’s gender Identification (GI) for Human-Robot Interaction (HRI). For this purpose, we perform speaker’s gender recognition based on Gaussian Mixture Model (GMM) and use robot platform called WEVER, which is a Ubiquitous Robotic Companion (URC) intelligent service robot developed at Intelligent Robot Research Division in Electronics and Telecommunication Research Institute (ETRI). Furthermore, we communicate with intelligent service robots through a Korean-based spontaneous speech recognition and text-independent speaker’s gender identification to provide a suitable service such as selection of preferable TV channel or music for the identified speaker’s gender. The experimental results obtained for ETRI speaker database reveal that the approach presented in this paper yields a good identification (94.9%) performance within 3 meter.