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From collocations to call-ocations: using linguistic methods to quantify animal call combinations


Bosshard, Alexandra B; Leroux, Maël; Lester, Nicholas A; Bickel, Balthasar; Stoll, Sabine; Townsend, Simon W (2022). From collocations to call-ocations: using linguistic methods to quantify animal call combinations. Behavioral Ecology and Sociobiology, 76:122.

Abstract

Emerging data in a range of non-human animal species have highlighted a latent ability to combine certain pre-existing calls together into larger structures. Currently, however, the quantification of context-specific call combinations has received less attention. This is problematic because animal calls can co-occur with one another simply through chance alone. One common approach applied in language sciences to identify recurrent word combinations is collocation analysis. Through comparing the co-occurrence of two words with how each word combines with other words within a corpus, collocation analysis can highlight above chance, two-word combinations. Here, we demonstrate how this approach can also be applied to non-human animal signal sequences by implementing it on artificially generated data sets of call combinations. We argue collocation analysis represents a promising tool for identifying non-random, communicatively relevant call combinations and, more generally, signal sequences, in animals.

Significance statement: Assessing the propensity for animals to combine calls provides important comparative insights into the complexity of animal vocal systems and the selective pressures such systems have been exposed to. Currently, however, the objective quantification of context-specific call combinations has received less attention. Here we introduce an approach commonly applied in corpus linguistics, namely collocation analysis, and show how this method can be put to use for identifying call combinations more systematically. Through implementing the same objective method, so-called call-ocations, we hope researchers will be able to make more meaningful comparisons regarding animal signal sequencing abilities both within and across systems.

Supplementary information: The online version contains supplementary material available at 10.1007/s00265-022-03224-3.

Keywords: Call combinations; Collocation analysis; Comparative approach; Non-random structure; Syntax

Abstract

Emerging data in a range of non-human animal species have highlighted a latent ability to combine certain pre-existing calls together into larger structures. Currently, however, the quantification of context-specific call combinations has received less attention. This is problematic because animal calls can co-occur with one another simply through chance alone. One common approach applied in language sciences to identify recurrent word combinations is collocation analysis. Through comparing the co-occurrence of two words with how each word combines with other words within a corpus, collocation analysis can highlight above chance, two-word combinations. Here, we demonstrate how this approach can also be applied to non-human animal signal sequences by implementing it on artificially generated data sets of call combinations. We argue collocation analysis represents a promising tool for identifying non-random, communicatively relevant call combinations and, more generally, signal sequences, in animals.

Significance statement: Assessing the propensity for animals to combine calls provides important comparative insights into the complexity of animal vocal systems and the selective pressures such systems have been exposed to. Currently, however, the objective quantification of context-specific call combinations has received less attention. Here we introduce an approach commonly applied in corpus linguistics, namely collocation analysis, and show how this method can be put to use for identifying call combinations more systematically. Through implementing the same objective method, so-called call-ocations, we hope researchers will be able to make more meaningful comparisons regarding animal signal sequencing abilities both within and across systems.

Supplementary information: The online version contains supplementary material available at 10.1007/s00265-022-03224-3.

Keywords: Call combinations; Collocation analysis; Comparative approach; Non-random structure; Syntax

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Comparative Language Science
Special Collections > NCCR Evolving Language
Special Collections > Centers of Competence > Center for the Interdisciplinary Study of Language Evolution
Dewey Decimal Classification:490 Other languages
890 Other literatures
410 Linguistics
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Life Sciences > Animal Science and Zoology
Uncontrolled Keywords:Animal Science and Zoology, Ecology, Evolution, Behavior and Systematics + Call combinations; Collocation analysis; Comparative approach; Non-random structure; Syntax
Language:English
Date:22 August 2022
Deposited On:22 Sep 2022 11:39
Last Modified:02 Oct 2022 01:53
Publisher:Springer
ISSN:0340-5443
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1007/s00265-022-03224-3
PubMed ID:36034316
Project Information:
  • : FunderSNSF
  • : Grant ID51NF40_180888
  • : Project TitleNCCR Evolving Language (phase I)
  • : FunderSNSF
  • : Grant IDPP00P3_163850
  • : Project TitleCombinatoriality in animal vocal communication

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