© Springer-Verlag Berlin Heidelberg 2012 Acoustic Bird Activity Detection on Real-Field Data

Abstract. We report on a research effort aiming at the development of an acoustic bird activity detector (ABAD), which plays an important role for au-tomating traditional biodiversity assessment studies – presently performed by human experts. The proposed on-line ABAD is considered an integral part of an automated system for acoustic identification of bird species, which is currently under development. In particular, taking advantage of real-field audio record-ings collected in the Hymettus Mountains east of Athens, we investigate the ap-plicability of various machine learning techniques for the needs of our ABAD, which is intended to run on a mobile device. Performance is reported in terms of recognition accuracy on audio-frame level, due to the restrictions imposed by the requirement of run-time decision making with limited memory and energy resources. We report recognition accuracy of approximately 86 % on a frame level, which is quite promising and encourages further research efforts in that direction