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      Animal vocal sequences: not the Markov chains we thought they were

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          Abstract

          Many animals produce vocal sequences that appear complex. Most researchers assume that these sequences are well characterized as Markov chains (i.e. that the probability of a particular vocal element can be calculated from the history of only a finite number of preceding elements). However, this assumption has never been explicitly tested. Furthermore, it is unclear how language could evolve in a single step from a Markovian origin, as is frequently assumed, as no intermediate forms have been found between animal communication and human language. Here, we assess whether animal taxa produce vocal sequences that are better described by Markov chains, or by non-Markovian dynamics such as the 'renewal process' (RP), characterized by a strong tendency to repeat elements. We examined vocal sequences of seven taxa: Bengalese finches Lonchura striata domestica, Carolina chickadees Poecile carolinensis, free-tailed bats Tadarida brasiliensis, rock hyraxes Procavia capensis, pilot whales Globicephala macrorhynchus, killer whales Orcinus orca and orangutans Pongo spp. The vocal systems of most of these species are more consistent with a non-Markovian RP than with the Markovian models traditionally assumed. Our data suggest that non-Markovian vocal sequences may be more common than Markov sequences, which must be taken into account when evaluating alternative hypotheses for the evolution of signalling complexity, and perhaps human language origins.

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          Most cited references50

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          Origins of Human Communication

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            Vocal Learning in Mammals

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              Recursive syntactic pattern learning by songbirds.

              Humans regularly produce new utterances that are understood by other members of the same language community. Linguistic theories account for this ability through the use of syntactic rules (or generative grammars) that describe the acceptable structure of utterances. The recursive, hierarchical embedding of language units (for example, words or phrases within shorter sentences) that is part of the ability to construct new utterances minimally requires a 'context-free' grammar that is more complex than the 'finite-state' grammars thought sufficient to specify the structure of all non-human communication signals. Recent hypotheses make the central claim that the capacity for syntactic recursion forms the computational core of a uniquely human language faculty. Here we show that European starlings (Sturnus vulgaris) accurately recognize acoustic patterns defined by a recursive, self-embedding, context-free grammar. They are also able to classify new patterns defined by the grammar and reliably exclude agrammatical patterns. Thus, the capacity to classify sequences from recursive, centre-embedded grammars is not uniquely human. This finding opens a new range of complex syntactic processing mechanisms to physiological investigation.
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                Author and article information

                Journal
                Proceedings of the Royal Society B: Biological Sciences
                Proc. R. Soc. B
                The Royal Society
                0962-8452
                1471-2954
                October 07 2014
                October 07 2014
                October 07 2014
                October 07 2014
                : 281
                : 1792
                : 20141370
                Affiliations
                [1 ]National Institute for Mathematical and Biological Synthesis, Knoxville, TN, USA
                [2 ]Hubbs SeaWorld Research Institute, San Diego, CA 92109, USA
                [3 ]Department of Psychology, University of Tennessee, Knoxville, TN, USA
                [4 ]Department of Physics and the Center for Neural Engineering, Penn State University, University Park, PA, USA
                [5 ]Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Sciencepark 904, 1098 XH, Amsterdam, The Netherlands
                [6 ]Pongo Foundation, Papenhoeflaan 91, 3421 XN, Oudewater, The Netherlands
                [7 ]Department of Biological Sciences, Florida International University, Miami, FL, USA
                Article
                10.1098/rspb.2014.1370
                25143037
                29ba71ab-3aef-4754-91ca-fc4e6136dbf5
                © 2014
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