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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 31 > No. 1: Thirty-First AAAI Conference On Artificial Intelligence

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


Proceedings:

No. 1: Thirty-First AAAI Conference On Artificial Intelligence

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 31

Track:

Student Abstract Track

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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 CassinÕs Vireos (Vireo cassinii), and show how behavioral contexts possibly affect bird song output.

DOI:

10.1609/aaai.v31i1.11073


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 31