A new study has found that the calls of many animals are more like human language.
For the study, the vocal sequences of seven different species of birds and mammals were analyzed by researchers and the analysis showed that the vocal sequences produced by the animals appear to be generated by complex statistical processes, similar to the language of the humans.
The researchers said that several animal species can produce complex vocalizations. For example: mockingbird can mimic over 100 distinct song types of different species, or the rock hyrax, whose long string of wails, chucks and snorts are similar to human.
The scientists said that the vocalizations suggest language-like characteristics but it is difficult to define and identify the complexity. The researchers said that the sequence of animal calls is generated by a simple random process, called a "Markov process."
The use of Markov process to examine animal vocalization means that the sequence of variables is dependent only on a finite number of preceding vocal elements. But the new study did not find evidence for a Markovian process and mathematical models were used to analyse the vocal sequences of chickadees, finches, bats, orangutans, killer whales, pilot whales and hyraxes.
The study revealed that most of the vocal sequences were more consistent with statistical models, which are e more complex than Markov processes and are similar to human language.
"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," said lead author Arik Kershenbaum, a postdoctoral fellow at the National Institute for Mathematical and Biological Synthesis in Knoxville.
"Uncovering the process underlying vocal sequence generation in animals may be critical to our understanding of the origin of language," Kershenbaum said.
The study is published in the journal Proceedings of the Royal Society B.