Intelligent sound source localization for dynamic environments

摘要

As robotic technology plays an increasing role in human lives, ¿robot audition¿, human-robot communication, is of great interest, and robot audition needs to be robust and adaptable for dynamic environments. This paper addresses sound source localization working in dynamic environments for robots. Previously, noise robustness and dynamic localized sound selection have been enormous issues for practical use. To correct the issues, a new localization system ¿Selective Attention System¿ is proposed. The system has four new functions: localization with Generalized EigenValue Decomposition of correlation matrices for noise robustness(¿Localization with GEVD¿), sound source cancellation and focus (¿Target Source Selection¿), human-like dynamic Focus of Attention (¿Dynamic FoA¿), and correlation matrix estimation for robotic head rotation (¿Correlation Matrix Estimation¿). All are achieved by the dynamic design of correlation matrices. The system is implemented into a humanoid robot, and the experimental validation is successfully verified even when the robot microphones move dynamically.