Classification of bioacoustic time series based on the combination of global and local decisions

Authors:
Christian Dietrich;Günther Palm;Klaus Riede;Friedhelm Schwenker
Affiliations:
Department of Neural Information Processing, University of Ulm, D-89069 Ulm, Germany;Department of Neural Information Processing, University of Ulm, D-89069 Ulm, Germany;Zoological Institute of Scientific Research and Museum Alexander Koenig, D-53113 Bonn, Germany;Department of Neural Information Processing, University of Ulm, D-89069 Ulm, Germany
Venue:
Pattern Recognition
Year:
2004

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Abstract

Automated classification of cricket songs from Thailand and Ecuador is the topic of this study. For this, the locations of pulses are determined and different features in the time and the frequency domain are extracted automatically from the time series. For the categorization of the sound patterns these features are combined through data fusion, temporal fusion and decision fusion. Local features and global features are distinguished. For the classification a fuzzy-k-nearest-neighbour classifier was used. Classification results for a data set containing songs of 28 different species are presented.