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Artificial neural networks were trained to discriminate between two different notes from the "chick-a-dee" call of the black-capped chickadee ͑Poecile atricapillus͒. An individual note was represented as a vector of nine summary features taken from note spectrograms. A network was trained to respond to exemplar notes of one type ͑e.g., A notes͒ and to fail to respond to exemplar notes of another type ͑e.g., B notes͒. After this training, the network was presented novel notes of the twodoi:10.1121/1.2211509 pmid:16938997 fatcat:67776tztwzgd7c6wgjyhtvnlxq