Not so random animal sounds may show a stepping stone towards language

The manner in which humans came to invent gestures and sounds, then developed these into words, then into language and eventually on into writing is a critical and fascinating story from our past that will probably never be fully known or understood. No doubt for humans there is also a connection to the invention of counting, the use of abstract symbols and the evolution of numeracy and the beginnings of the languages of mathematics.The timeline of these evolutions are also in much doubt. Possibly gestures and sounds go back 300,000 years (or even further), but language was established among humans only by about 50,000 years ago. Words and their earlier sounds must have come much, much earlier and writing very much later. Cave paintings around 30,000 years ago may represent the period when abstract symbolism was taking off. It is thought that writing did not come until agriculture expanded – perhaps from about 12,000 years ago.

Now research on animal sounds suggests that for some species the sounds they make are not as random as they were originally thought to be. They exhibit levels of complexity which are suggestive of stepping-stones along the long road to grammar and language. Such steps may have assisted humans from moving from sounds and words to context-free grammars and thence to language.

The sequence in humans – I speculate – could have been:

(300KYA) gestures>> sounds>> (smiles, laughter?)>> words>> ..(unknown steps)>> simple grammar>> context-free grammar>> language>> symbols>> abstract symbols>> writing (12KYA)

Kershenbaum A, Bowles A, Freeburg T, Dezhe J, Lameira A, Bohn K. 2014. Animal vocal sequences: Not the Markov chains we thought they were. Proceedings of the Royal Society B. rspb.royalsocietypublishing.or… .1098/rspb.2014.1370

PhysOrg reports:

The study, published today in the journal Proceedings of the Royal Society B, analyzed the vocal sequences of seven different species of birds and mammals and found that the vocal sequences produced by the animals appear to be generated by complex statistical processes, more akin to human language. ….

Many species of animals produce complex vocalizations – consider the mockingbird, for example, which can mimic over 100 distinct song types of different species, or the rock hyrax, whose long string of wails, chucks and snorts signify male territory. But while the vocalizations suggest language-like characteristics, scientists have found it difficult to define and identify the complexity.

Typically, scientists have assumed that the sequence of animal calls is generated by a simple random process, called a “Markov process.” Using the Markov process to examine animal vocalization means that the sequence of variables—in this case, the vocal elements—is dependent only on a finite number of preceding vocal elements, making the process fairly random and far different from the complexity inherent in human language. ……. 

…… the study found no evidence for a Markovian process. The researchers used mathematical models to analyze the vocal sequences of chickadees, finches, bats, orangutans, killer whales, pilot whales and hyraxes, and found most of the vocal sequences were more consistent with statistical models that are more complex than Markov processes and more language-like. …… 

“Language is the biggest difference that separates humans from animals evolutionarily, but multiple studies are finding more and more stepping stones that seem to bridge this gap. Uncovering the process underlying vocal sequence generation in animals may be critical to our understanding of the origin of language,” said lead author Arik Kershenbaum, a postdoctoral fellow at the National Institute for Mathematical and Biological Synthesis.

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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One Response to “Not so random animal sounds may show a stepping stone towards language”

  1. Not so random animal sounds may show a stepping stone towards language | 6,000 Generations Says:

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