Understanding auditory scenes is important when deploying intelligent robots and systems in real-world environments. We believe that robot audition can better recognize acoustic events in the field as compared to conventional methods such as human observation or recording using single-channel microphone array. We are particularly interested in acoustic interactions among songbirds. Birds do not always vocalize at random, for example, but may instead divide a soundscape so that they avoid overlapping their songs with those of other birds. To understand such complex interaction processes, we must collect much spatiotemporal data in which multiple individuals and species are singing simultaneously. However, it is costly and difficult to annotate many or long recorded tracks manually to detect their interactions. In order to solve this problem, we are developing HARKBird, an easily-available and portable system consisting of a laptop PC with open-source software for robot audition HARK (Honda Research Institute Japan Audition for Robots with Kyoto University) together with a lowcost and commercially available microphone array. HARKBird enables us to extract the songs of multiple individuals from recordings automatically. In this paper, we introduce the current status of our project and report preliminary results of recording experiments in two different types of forests – one in the USA and the other in Japan-using this system to automatically estimate the direction of arrival of the songs of multiple birds, and separate them from the recordings. We also discuss asymmetries among species in terms of their tendency to partition temporal resources.
ASJC Scopus subject areas
- コンピュータ サイエンス（全般）