Content-based Retreival from Unstructured Audio Databases using an Ecological Acoustics Taxonomy
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Author(s)
Herrera, Perfecto
Schirosa, Mattia
Kersten, Stefan
Janer, Jordi
Roma, Gerard
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Abstract
In this paper we describe a method to search for environmental
sounds in unstructured databases with user-submitted material.
The goal of the project is to facilitate the design of soundscapes in
virtual environments. We analyze the use of a Support Vector Machine
(SVM) as a learning algorithm to classify sounds according
to a general sound events taxonomy based on ecological acoustics.
In our experiments, we obtain accuracies above 80% using crossvalidation.
Finally, we present a web prototype that integrates the
classifier to rank sounds according to their relation to the taxonomy
concepts.
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Date
2010-06
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Text
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Proceedings