Semantic Inference of Bird Songs Using Dynamic Bayesian Networks

Authors

  • Keisuke Daimon Nagoya University
  • Richard Hedley University of California, Los Angeles
  • Charles Taylor University of California, Los Angeles

DOI:

https://doi.org/10.1609/aaai.v31i1.11073

Keywords:

Dynamic Bayesian network, Semantic inference, Cassin's Vireo, Bird song

Abstract

Knowledge representation and natural language processing are core interests to the field of artificial intelligence (AI). While most research has been directed toward machines and humans, the principles and methods developed for AI might be extended to other species as well. Birds frequently behave in a manner that is intelligent and convey information in their vocalizations that is meaningful to others. In this paper we report on a method combining clustering and dynamic Bayesian networks to describe the semantics of songs among Cassin’s Vireos (Vireo cassinii), and show how behavioral contexts possibly affect bird song output.

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Published

2017-02-12

How to Cite

Daimon, K., Hedley, R., & Taylor, C. (2017). Semantic Inference of Bird Songs Using Dynamic Bayesian Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.11073