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

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.