Quantifying similarity in animal vocal sequences: Which metric performs best?

<jats:title>Summary</jats:title><jats:p> <jats:list> <jats:list-item><jats:p>Many animals communicate using sequences of discrete acoustic elements which can be complex, vary in their degree of stereotypy, and are potentially open‐ended. Variation in sequences can...

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Main Authors: Kershenbaum, A, Garland, EC
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2015
Subjects:
Online Access:https://www.repository.cam.ac.uk/handle/1810/248821
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spelling ftunivcam:oai:www.repository.cam.ac.uk:1810/248821 2024-02-04T10:01:04+01:00 Quantifying similarity in animal vocal sequences: Which metric performs best? Kershenbaum, A Garland, EC 2015 application/pdf https://www.repository.cam.ac.uk/handle/1810/248821 English eng eng Wiley http://dx.doi.org/10.1111/2041-210x.12433 Methods in Ecology and Evolution https://www.repository.cam.ac.uk/handle/1810/248821 animal communication edit distance Markov sequence stochastic processes vocal Article 2015 ftunivcam 2024-01-11T23:28:11Z <jats:title>Summary</jats:title><jats:p> <jats:list> <jats:list-item><jats:p>Many animals communicate using sequences of discrete acoustic elements which can be complex, vary in their degree of stereotypy, and are potentially open‐ended. Variation in sequences can provide important ecological, behavioural or evolutionary information about the structure and connectivity of populations, mechanisms for vocal cultural evolution and the underlying drivers responsible for these processes. Various mathematical techniques have been used to form a realistic approximation of sequence similarity for such tasks.</jats:p></jats:list-item> <jats:list-item><jats:p>Here, we use both simulated and empirical data sets from animal vocal sequences (rock hyrax, <jats:italic><jats:styled-content style="fixed-case">P</jats:styled-content>rocavia capensis</jats:italic>; humpback whale, <jats:italic><jats:styled-content style="fixed-case">M</jats:styled-content>egaptera novaeangliae</jats:italic>; bottlenose dolphin, <jats:italic><jats:styled-content style="fixed-case">T</jats:styled-content>ursiops truncatus</jats:italic>; and <jats:styled-content style="fixed-case">C</jats:styled-content>arolina chickadee, <jats:italic><jats:styled-content style="fixed-case">P</jats:styled-content>oecile carolinensis</jats:italic>) to test which of eight sequence analysis metrics are more likely to reconstruct the information encoded in the sequences, and to test the fidelity of estimation of model parameters, when the sequences are assumed to conform to particular statistical models.</jats:p></jats:list-item> <jats:list-item><jats:p>Results from the simulated data indicated that multiple metrics were equally successful in reconstructing the information encoded in the sequences of simulated individuals (<jats:styled-content ... Article in Journal/Newspaper Humpback Whale Apollo - University of Cambridge Repository
institution Open Polar
collection Apollo - University of Cambridge Repository
op_collection_id ftunivcam
language English
topic animal communication
edit distance
Markov
sequence
stochastic processes
vocal
spellingShingle animal communication
edit distance
Markov
sequence
stochastic processes
vocal
Kershenbaum, A
Garland, EC
Quantifying similarity in animal vocal sequences: Which metric performs best?
topic_facet animal communication
edit distance
Markov
sequence
stochastic processes
vocal
description <jats:title>Summary</jats:title><jats:p> <jats:list> <jats:list-item><jats:p>Many animals communicate using sequences of discrete acoustic elements which can be complex, vary in their degree of stereotypy, and are potentially open‐ended. Variation in sequences can provide important ecological, behavioural or evolutionary information about the structure and connectivity of populations, mechanisms for vocal cultural evolution and the underlying drivers responsible for these processes. Various mathematical techniques have been used to form a realistic approximation of sequence similarity for such tasks.</jats:p></jats:list-item> <jats:list-item><jats:p>Here, we use both simulated and empirical data sets from animal vocal sequences (rock hyrax, <jats:italic><jats:styled-content style="fixed-case">P</jats:styled-content>rocavia capensis</jats:italic>; humpback whale, <jats:italic><jats:styled-content style="fixed-case">M</jats:styled-content>egaptera novaeangliae</jats:italic>; bottlenose dolphin, <jats:italic><jats:styled-content style="fixed-case">T</jats:styled-content>ursiops truncatus</jats:italic>; and <jats:styled-content style="fixed-case">C</jats:styled-content>arolina chickadee, <jats:italic><jats:styled-content style="fixed-case">P</jats:styled-content>oecile carolinensis</jats:italic>) to test which of eight sequence analysis metrics are more likely to reconstruct the information encoded in the sequences, and to test the fidelity of estimation of model parameters, when the sequences are assumed to conform to particular statistical models.</jats:p></jats:list-item> <jats:list-item><jats:p>Results from the simulated data indicated that multiple metrics were equally successful in reconstructing the information encoded in the sequences of simulated individuals (<jats:styled-content ...
format Article in Journal/Newspaper
author Kershenbaum, A
Garland, EC
author_facet Kershenbaum, A
Garland, EC
author_sort Kershenbaum, A
title Quantifying similarity in animal vocal sequences: Which metric performs best?
title_short Quantifying similarity in animal vocal sequences: Which metric performs best?
title_full Quantifying similarity in animal vocal sequences: Which metric performs best?
title_fullStr Quantifying similarity in animal vocal sequences: Which metric performs best?
title_full_unstemmed Quantifying similarity in animal vocal sequences: Which metric performs best?
title_sort quantifying similarity in animal vocal sequences: which metric performs best?
publisher Wiley
publishDate 2015
url https://www.repository.cam.ac.uk/handle/1810/248821
genre Humpback Whale
genre_facet Humpback Whale
op_relation https://www.repository.cam.ac.uk/handle/1810/248821
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