Swedish e-Science Academy 2016
We have the pleasure of inviting the community to the Swedish e-Science Academy 2016.
Read more …
NEW extended deadline for registration: September 30 at 14 hrs.
eSSENCE research in focus
Classification Tool for Bird Singing
Understanding communication and signalling has long been strived for in studies of animal behaviour. Many songbirds have a variable and complex song, closely connected to territory defence and reproductive success. An interdisciplinary group at Lund University has developed a novel, automated method for detection and classification of syllables in birdsong. The method allows analyses such as (1) determining repertoire size within an individual, (2) comparing song similarity between individuals within as well as between populations of a species and (3) comparing songs of different species (e.g. for species recognition). Using a single song from a great reed warbler, Acrocephalus arundinaceus, recorded in the wild, the proposed algorithm is evaluated by means of comparison to manual auditory and visual (spectrogram) song investigation by a human expert and to standard song analysis methods. The birdsong analysis approach conforms well to manual classification and, moreover, outperforms the hitherto widely used methods. The algorithm is a methodological step forward for analyses of song (syllable) repertoires of birds singing with high complexity.