Unsupervised Acoustic Classification of Bird Species Using Hierarchical Self-organizing Maps

In this paper, we propose the application of hierarchical self-organizing maps to the unsupervised acoustic classification of bird species. We describe a series of experiments on the automated categorization of tropical antbirds from their songs. Experimental results showed that accurate classification can be achieved using the proposed model. In addition, we discuss how categorization capabilities could be deployed in sensor arrays.

[1]  Teuvo Kohonen,et al.  Self-Organizing Maps, Second Edition , 1997, Springer Series in Information Sciences.

[2]  Charles E. Taylor,et al.  Self-organization in sensor networks , 2004, J. Parallel Distributed Comput..

[3]  L. Munari.  How the body shapes the way we think — a new view of intelligence , 2009 .

[4]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[5]  Wolfgang Banzhaf,et al.  Advances in Artificial Life , 2003, Lecture Notes in Computer Science.

[6]  Gregory J. Pottie,et al.  Instrumenting the world with wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[7]  Yuan Yao,et al.  The Learning and Emergence of Mildly Context Sensitive Languages , 2003, ECAL.

[8]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[9]  C. Allen,et al.  The Cognitive Animal: Empirical and Theoretical Perspectives on Animal Cognition , 2002 .

[10]  Anders Krogh,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[11]  Douglas A. Nelson,et al.  The Importance of Invariant and Distinctive Features in Species Recognition of Bird Song , 1989 .

[12]  Charles E. Taylor.  From Cognition in Animals to Cognition in Superorganisms , 2000 .

[13]  Rolf Pfeifer,et al.  How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books) , 2006 .

[14]  P. Slater,et al.  Bird Song: Biological Themes and Variations , 1995 .

[15]  C. Taylor,et al.  Adaptive communication among collaborative agents: preliminary results with symbol grounding , 2003, Artificial Life and Robotics.