ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2012
Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning.
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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66 citing papers in PubMed.
- Third-order self-embedded vocal motifs in wild orangutans, and the selective evolution of recursion.Annals of the New York Academy of Sciences · 2025Article
- Non-adjacent dependency processing (or lack thereof) in bonobos: an artificial grammar experiment.Royal Society open science · 2025Article
- Neighbour-stranger discrimination in an African wood dove inhabiting equatorial rainforest.Scientific reports · 2024Article
- Nonadjacent dependencies and sequential structure of chimpanzee action during a natural tool-use task.PeerJ · 2024Article
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- A test of memory for stimulus sequences in great apes.PloS one · 2023Article
- The evolution of hierarchical structure building capacity for language and music: a bottom-up perspective.Primates; journal of primatology · 2022Review
- Overlooked evidence for semantic compositionality and signal reduction in wild chimpanzees (Pan troglodytes).Animal cognition · 2022Article
- From collocations to call-ocations: using linguistic methods to quantify animal call combinations.Behavioral ecology and sociobiology · 2022Article
- Toward a Computational Neuroethology of Vocal Communication: From Bioacoustics to Neurophysiology, Emerging Tools and Future Directions.Frontiers in behavioral neuroscience · 2021Review
- Nonhuman and Nonhuman-Human Communication: Some Issues and Questions.Frontiers in psychology · 2021Review
- Higher-Order Musical Temporal Structure in Bird Song.Frontiers in psychology · 2021Article
- Emergence of abstract rules in the primate brain.Nature reviews. Neuroscience · 2020Review
- Structured Sequence Learning: Animal Abilities, Cognitive Operations, and Language Evolution.Topics in cognitive science · 2020Review
- How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning.Neuroscience and biobehavioral reviews · 2020Review
- Baboons (Papio papio) Process a Context-Free but Not a Context-Sensitive Grammar.Scientific reports · 2020Article
- Positional encoding in cotton-top tamarins (Saguinus oedipus).Animal cognition · 2019Article
- Capacities and neural mechanisms for auditory statistical learning across species.Hearing research · 2019Review
- Ontogeny of vocal rhythms in harbor seal pups: an exploratory study.Current zoology · 2019Article
6 more citing papers are in PubMed but not listed here.
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Abstract
The domain of syntax is seen as the core of the language faculty and as the most critical difference between animal vocalizations and language. We review evidence from spontaneously produced vocalizations as well as from perceptual experiments using artificial grammars to analyse animal syntactic abilities, i.e. abilities to produce and perceive patterns following abstract rules. Animal vocalizations consist of vocal units (elements) that are combined in a species-specific way to create higher order strings that in turn can be produced in different patterns. While these patterns differ between species, they have in common that they are no more complex than a probabilistic finite-state grammar. Experiments on the perception of artificial grammars confirm that animals can generalize and categorize vocal strings based on phonetic features. They also demonstrate that animals can learn about the co-occurrence of elements or learn simple 'rules' like attending to reduplications of units. However, these experiments do not provide strong evidence for an ability to detect abstract rules or rules beyond finite-state grammars. Nevertheless, considering the rather limited number of experiments and the difficulty to design experiments that unequivocally demonstrate more complex rule learning, the question of what animals are able to do remains open.
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