Sound Source Localization for Robotic Applications

Intuitive human robot interfaces like speech or gesture recognition are essential for gaining acceptance for robots in daily life. However, such interaction requires that the robot detects the human’s intention to interact, tracks his position and keeps its sensor systems in an optimal configuration. Audio is a suitable modality for such task as it allows for detecting a speaker in arbitrary positions around the robot. In this paper, we present an extension of our proposed sound source localization approach Motion Model Enhanced MUltiple SIgnal Classification (MME-MUSIC) for segmenting speech input. We evaluate the system with speech captured under real conditions in an experimental setup and show the use of our estimation in real applications.