Journals Proceedings

Abstract

This paper presents a study of automatic detection and recognition of bird species based on bioacoustics. The energy distribution in different frequency bands varies quite significantly among different birds’ sounds. Energy in various frequency bands is extracted using wavelet packet transform and k-nearest neighbor algorithm is used for classification. In our experiment, classification accuracy of 91% is achieved for the classification of eight bird species. A total of 307 bird sound files are used to train/test the system.