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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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 |
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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 |
_version_ |
1789966718249992192 |