Using an artificial neural network to classify black-capped chickadee (Poecile atricapillus) call note types.

@article{Dawson2006UsingAA,
  title={Using an artificial neural network to classify black-capped chickadee (Poecile atricapillus) call note types.},
  author={Michael R. W. Dawson and Isabelle Charrier and Christopher B. Sturdy},
  journal={The Journal of the Acoustical Society of America},
  year={2006},
  volume={119 5 Pt 1},
  pages={
          3161-72
        }
}
The "chick-a-dee" call of the black-capped chickadee (Poecile atricapillus) contains four note types, A, B, C, and D that have important functional roles. This provides strong motivation for studying the classification of acoustic components of the call into different note types. In this paper, the spectrograms from a sample of A, B, and C notes (370 in total) were each described as a set of 9 summary features. An artificial neural network was trained to identify note type on the basis of these… Expand
Artificial neural network discrimination of black-capped chickadee (Poecile atricapillus) call notes.
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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, and results were very similar to those observed in birds that were trained in an analogous task. Expand
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