Semantic Inference of Bird Songs Using Dynamic Bayesian Networks

Semantic Inference of Bird Songs Using Dynamic Bayesian Networks
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使用动态贝叶斯网络对鸟鸣进行语义推理

DOI：
10.1609/aaai.v31i1.11073
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发表时间：
2017
期刊：
--
影响因子：
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通讯作者：
C. Taylor
C. Taylor
中科院分区：
--
文献类型：
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作者：
Keisuke Daimon;R. Hedley;C. Taylor

文献摘要

被引文献

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知识表示和自然语言处理是人工智能领域的核心问题。虽然大多数研究都是针对机器和人类的，但为人工智能开发的原理和方法也可能扩展到其他物种。鸟类经常以一种聪明的方式行事，并在它们的声音中传达对其他人有意义的信息。在本文中，我们报告的方法相结合的聚类和动态贝叶斯网络来描述的语义之间的卡辛的绿鹃（Vireo cassinii）的歌曲，并显示如何行为的背景下可能会影响鸟鸣输出。
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.