Bioacoustics Research Summary

My diploma thesis evolved during a collaborative project of the Multimedia Signal Processing Group of Bonn University and the Animal Sound Archive in Berlin. (Long term) monitoring recordings have been performed in a nature conservation area at Parstein Lake, Brandenburg, Germany. Besides a general description of the Project, the thesis focuses on general signal processing algorithms for bird songs featuring periodic structures. These are currently used to identify the Savi’s Warbler calls within such recordings. Furthermore, techniques are provided for the analysis of more complex rhythmic structures. The design of the algorithms heavily orients towards robust recognition of the repetitive song, as the undirected recordings are subject to varying grades of (weather-induced) noise. Key technologies include: FFT, Novelty Curves, Autocorrelation, Hidden Markov Models.

In: Aucouturier, Jean-Julien (Ed.) et al.: Pattern recognition of non-speech audio, S. 1524-1534

From December 7 through 10, 2007, an international expert meeting on IT-based detection of bioacoustic patterns was held at the facilities of the International Academy for Nature Conservation on the Isle of Vilm in the Baltic Sea. The meeting was held under the patronage of the German Federal Agency for Nature Conservation (Bundesamt für Naturschutz, BfN) in the context of a research project on bioacoustic pattern recognition. [...] The topics of the meeting covered both the current knowledge on acoustic pattern recognition in bioacoustic signals and the application of bioacoustic methods for purposes of the monitoring of wild animals. This publication contains expanded versions of the talks given during the meeting [...]. The articles cover a wide variety of animal species from insects and frogs to birds, from whales to bats. Monitoring locations reach from the densely populated centre of Europe to the out-backs of Australia, from the Mediterranean Sea to Antarctica.