Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds

The singing of juvenile songbirds is highly variable and not well stereotyped, a feature that makes it difficult to analyze with existing computational techniques. We present here a method suitable for analyzing such vocalizations, windowed spectral pattern recognition (WSPR). Rather than performing...

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Main Authors: Cameron D. Wellock, George N. Reeke
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Computational Intelligence and Neuroscience
Online Access:http://dx.doi.org/10.1155/2012/261010
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spelling doaj-db7bc4b39f6e4d1da6a3cf5d2e7b6a492020-11-24T22:48:18ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52651687-52732012-01-01201210.1155/2012/261010261010Quantitative Tools for Examining the Vocalizations of Juvenile SongbirdsCameron D. Wellock0George N. Reeke1Laboratory of Biological Modeling, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USALaboratory of Biological Modeling, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USAThe singing of juvenile songbirds is highly variable and not well stereotyped, a feature that makes it difficult to analyze with existing computational techniques. We present here a method suitable for analyzing such vocalizations, windowed spectral pattern recognition (WSPR). Rather than performing pairwise sample comparisons, WSPR measures the typicality of a sample against a large sample set. We also illustrate how WSPR can be used to perform a variety of tasks, such as sample classification, song ontogeny measurement, and song variability measurement. Finally, we present a novel measure, based on WSPR, for quantifying the apparent complexity of a bird’s singing.http://dx.doi.org/10.1155/2012/261010
collection DOAJ
language English
format Article
sources DOAJ
author Cameron D. Wellock
George N. Reeke
spellingShingle Cameron D. Wellock
George N. Reeke
Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds
Computational Intelligence and Neuroscience
author_facet Cameron D. Wellock
George N. Reeke
author_sort Cameron D. Wellock
title Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds
title_short Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds
title_full Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds
title_fullStr Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds
title_full_unstemmed Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds
title_sort quantitative tools for examining the vocalizations of juvenile songbirds
publisher Hindawi Limited
series Computational Intelligence and Neuroscience
issn 1687-5265
1687-5273
publishDate 2012-01-01
description The singing of juvenile songbirds is highly variable and not well stereotyped, a feature that makes it difficult to analyze with existing computational techniques. We present here a method suitable for analyzing such vocalizations, windowed spectral pattern recognition (WSPR). Rather than performing pairwise sample comparisons, WSPR measures the typicality of a sample against a large sample set. We also illustrate how WSPR can be used to perform a variety of tasks, such as sample classification, song ontogeny measurement, and song variability measurement. Finally, we present a novel measure, based on WSPR, for quantifying the apparent complexity of a bird’s singing.
url http://dx.doi.org/10.1155/2012/261010
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