Unsupervised acoustic classification of bird species using hierarchical self-organizing maps

被引：0

作者：

Vallejo, Edgar E. ^{[1
]}

Cody, Martin L. ^{[2
]}

Taylor, Charles E. ^{[2
]}

机构：

[1] ITESM CEM, Dept Comp Sci, Atizapan De Zaragoza 52926, Edo Mexico, Mexico

[2] Univ Calif Los Angeles, Dept Ecol & Evolut Biol, Los Angeles, CA 90095 USA

来源：

PROGRESS IN ARTIFICIAL LIFE, PROCEEDINGS | 2007年 / 4828卷

基金：

美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：212 / +

页数：2

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