Detecting bird sounds in a complex acoustic environment and application to bioacoustic monitoring

Publication Type:Journal Article
Year of Publication:2009
Authors:R. Bardeli, Wolff, D., Kurth, F., Koch, M., Tauchert, K. H., Frommolt, K. H.
Journal:Pattern Recognition Letters
Date Published:September
Keywords:asr, bioacoustics, birds, monitoring, neuroinofrmatics

Trends in bird population sizes are an important indicator in nature conservation but measuring such sizes is a very difficult, labour intensive process. Enormous progress in audio signal processing and pattern recognition in recent years makes it possible to incorporate automated methods into the detection of bird vocalisations. These methods can be employed to support the census of population sizes. We report about a study testing the feasibility of bird monitoring supported by automatic bird song detection. In particular, we describe novel algorithms for the detection of the vocalisations of two endangered bird species and show how these can be used in automatic habitat mapping. These methods are based on detecting temporal patterns in a given frequency band typical for the species. Special effort is put into the suppression of the noise present in real-world audio scenes. Our results show that even in real-world recording conditions high recognition rates with a tolerable rate of false positive detections are possible.

Scratchpads developed and conceived by (alphabetical): Ed Baker, Katherine Bouton Alice Heaton Dimitris Koureas, Laurence Livermore, Dave Roberts, Simon Rycroft, Ben Scott, Vince Smith