Sound source separation and automatic speech recognition for moving sources

Abstract

This paper addresses sound source separation and speech recognition for moving sound sources. Real-world applications such as robots should cope with both moving and stationary sound sources. However, most studies assume only stationary sound sources. We introduce three key techniques to cope with moving sources, that is, Adaptive Step-size control (AS), Optima Controlled Recursive Average (OCRA), and Separation Parameter Switching (SPS). We implemented a real-time robot audition system with these techniques for our humanoid robot with an 8ch microphone array by using HARK which is our open-source software for robot audition. Preliminary results show that the performance of recognition of moving sound sources improved drastically, and also the performance of the system is shown through two speech dialog scenarios which requires sound source separation and automatic speech recognition for moving sources.