Individual vocal recognition across taxa : a review of the literature and a look into the future
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Individual vocal recognition (IVR) has been well studied in mammals and birds. These studies have primarily delved into understanding IVR in specific limited contexts (e.g. parent–offspring and mate recognition) where individuals discriminate one individual from all others. However, little research has examined IVR in more socially demanding circumstances, such as when an individual discriminates all individuals in their social or familial group apart. In this review, we describe what IVR is and suggest splitting studies of IVR into two general types based on what questions they answer (IVR-singular, and IVR-multiple). We explain how we currently test for IVR, and many of the benefits and drawbacks of different methods. We address why IVR is so prevalent in the animal kingdom, and the circumstances in which it is often found. Finally, we explain current weaknesses in IVR research including temporality, specificity, and taxonomic bias, and testing paradigms, and provide some solutions to address these weaknesses.
This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.
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CARLSON, Nora V., Elizabeth McKenna KELLY, Iain D. COUZIN, 2020. Individual vocal recognition across taxa : a review of the literature and a look into the future. In: Philosophical Transactions of the Royal Society of London, Series B : Biological Sciences. Royal Society of London. 2020, 375(1802), 20190479. ISSN 0962-8436. eISSN 1471-2970. Available under: doi: 10.1098/rstb.2019.0479BibTex
@article{Carlson2020-07-06Indiv-49954, year={2020}, doi={10.1098/rstb.2019.0479}, title={Individual vocal recognition across taxa : a review of the literature and a look into the future}, number={1802}, volume={375}, issn={0962-8436}, journal={Philosophical Transactions of the Royal Society of London, Series B : Biological Sciences}, author={Carlson, Nora V. and Kelly, Elizabeth McKenna and Couzin, Iain D.}, note={Article Number: 20190479} }
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