Design and assessment of multiple-sound source localization using microphone arrays

This paper addresses 2D sound source localization using multiple microphone arrays with the future aim to be applied to outdoor environments. To achieve such sound source localization, there are two main issues to overcome. One is the lack of knowledge about how to design the system, since the localization performance depends on resolution of the array's Transfer Function, the number of used microphone arrays, signal-to-noise ratio and the target sound's frequency characteristics. We conduct a thorough analysis of the localization results with different simulation conditions. The other problem is the distinction between multiple sound sources, which is directly related to the appearance of outliers in the localization process of these sounds. To solve this issue, we propose an outlier removal method, taking sound property of the observed sounds into consideration. As the application scenario of the simulations, we selected bird song analysis, which provides a challenging environment in terms of constantly changing signal-to-noise ratio and relative sensor-to-target position. When the task is automated, robust robot audition technology can be established, possibly advancing one step closer to creating a fully automated bird song analysis system. We established a prototype system using the proposed method. We present several simulation results followed by a discussion on the issues, leading to establishing system design guidelines that ensure a predictable performance.