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Acoustic sequences in non-human animals: A tutorial review and prospectus

Acoustic sequences in non-human animals: A tutorial review and prospectus
Acoustic sequences in non-human animals: A tutorial review and prospectus

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise-let alone understand-the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.

Acoustic communication, Information, Information theory, Machine learning, Markov model, Meaning, Network analysis, Sequence analysis, Vocalisation
1464-7931
13-52
Kershenbaum, Arik
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Carter, Gerald
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Coen, Michael
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Doyle, Laurance
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Gustison, Morgan
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Huetz, Chloé
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Hughes, Melissa
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Hyland Bruno, Julia
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Johnson, Michael
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Ju, Chenghui
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Karnowski, Jeremy
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Lohr, Bernard
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Shiu, Yu
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Taylor, Charles
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Vallejo, Edgar E.
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Waller, Sara
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Zamora-Gutierrez, Veronica
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Kershenbaum, Arik
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Blumstein, Daniel T.
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Roch, Marie A.
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Akçay, Çağlar
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Backus, Gregory
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Bohn, Kirsten
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Carter, Gerald
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Cäsar, Cristiane
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Coen, Michael
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Hughes, Melissa
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Hyland Bruno, Julia
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Ilany, Amiyaal
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Johnson, Michael
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Ju, Chenghui
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Karnowski, Jeremy
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Lohr, Bernard
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Manser, Marta B.
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Mccowan, Brenda
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Mercado, Eduardo
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Piel, Alex
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Rice, Megan
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Salmi, Roberta
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Sasahara, Kazutoshi
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Sayigh, Laela
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Shiu, Yu
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Taylor, Charles
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Vallejo, Edgar E.
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Waller, Sara
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Zamora-Gutierrez, Veronica
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Kershenbaum, Arik, Blumstein, Daniel T., Roch, Marie A., Akçay, Çağlar, Backus, Gregory, Bee, Mark A., Bohn, Kirsten, Cao, Yan, Carter, Gerald, Cäsar, Cristiane, Coen, Michael, Deruiter, Stacy L., Doyle, Laurance, Edelman, Shimon, Ferrer-i-Cancho, Ramon, Freeberg, Todd M., Garland, Ellen C., Gustison, Morgan, Harley, Heidi E., Huetz, Chloé, Hughes, Melissa, Hyland Bruno, Julia, Ilany, Amiyaal, Jin, Dezhe Z., Johnson, Michael, Ju, Chenghui, Karnowski, Jeremy, Lohr, Bernard, Manser, Marta B., Mccowan, Brenda, Mercado, Eduardo, Narins, Peter M., Piel, Alex, Rice, Megan, Salmi, Roberta, Sasahara, Kazutoshi, Sayigh, Laela, Shiu, Yu, Taylor, Charles, Vallejo, Edgar E., Waller, Sara and Zamora-Gutierrez, Veronica (2016) Acoustic sequences in non-human animals: A tutorial review and prospectus. Biological Reviews, 91 (1), 13-52. (doi:10.1111/brv.12160).

Record type: Article

Abstract

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise-let alone understand-the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.

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More information

Published date: 1 February 2016
Additional Information: Publisher Copyright: © 2016 Cambridge Philosophical Society.
Keywords: Acoustic communication, Information, Information theory, Machine learning, Markov model, Meaning, Network analysis, Sequence analysis, Vocalisation

Identifiers

Local EPrints ID: 486695
URI: http://eprints.soton.ac.uk/id/eprint/486695
ISSN: 1464-7931
PURE UUID: 61696bf9-fc14-440b-9a85-361179de77f5
ORCID for Michael Johnson: ORCID iD orcid.org/0000-0002-5566-6147
ORCID for Veronica Zamora-Gutierrez: ORCID iD orcid.org/0000-0003-0661-5180

Catalogue record

Date deposited: 01 Feb 2024 17:50
Last modified: 11 Jul 2024 02:17

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Contributors

Author: Arik Kershenbaum
Author: Daniel T. Blumstein
Author: Marie A. Roch
Author: Çağlar Akçay
Author: Gregory Backus
Author: Mark A. Bee
Author: Kirsten Bohn
Author: Yan Cao
Author: Gerald Carter
Author: Cristiane Cäsar
Author: Michael Coen
Author: Stacy L. Deruiter
Author: Laurance Doyle
Author: Shimon Edelman
Author: Ramon Ferrer-i-Cancho
Author: Todd M. Freeberg
Author: Ellen C. Garland
Author: Morgan Gustison
Author: Heidi E. Harley
Author: Chloé Huetz
Author: Melissa Hughes
Author: Julia Hyland Bruno
Author: Amiyaal Ilany
Author: Dezhe Z. Jin
Author: Michael Johnson ORCID iD
Author: Chenghui Ju
Author: Jeremy Karnowski
Author: Bernard Lohr
Author: Marta B. Manser
Author: Brenda Mccowan
Author: Eduardo Mercado
Author: Peter M. Narins
Author: Alex Piel
Author: Megan Rice
Author: Roberta Salmi
Author: Kazutoshi Sasahara
Author: Laela Sayigh
Author: Yu Shiu
Author: Charles Taylor
Author: Edgar E. Vallejo
Author: Sara Waller
Author: Veronica Zamora-Gutierrez ORCID iD

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